From mgalle at gmail.com Wed Dec 1 03:02:20 2021 From: mgalle at gmail.com (=?UTF-8?Q?Matthias_Gall=C3=A9?=) Date: Wed, 1 Dec 2021 09:02:20 +0100 Subject: Connectionists: internship Naver Labs Europe: speech+text Message-ID: Dear all, This is an internship opportunity for a talented student interested in improving machine translation with speech data. application at: https://europe.naverlabs.com/job/using-monolingual-speech-data-to-improve-multilingual-translation-models-internship/ **Using monolingual speech data to improve multilingual translation models** A large part of today's 7000+ languages do not have a writing system, and many more only have a very small amount of available textual data. As an example, while wikipedia exists in 264 languages, only 100 of those have more than 5000 pages. In this internship we plan to investigate how to leverage monolingual speech data to improve multilingual text translation systems. For that, we will base ourselves on existing work in speech-to-text translation: models that start from large pre-trained models (e.g., [1, 2]) as well as our previous experience in end-to-end speech translation models [3] and the use of monolingual data to improve translation systems for unseen languages [4]. At NLE we proud ourselves of very tight collaborations with our interns, consisting of very regular meetings and joint brainstorming and development. Interns are integrated into existing teams and participate actively in the scientific activities of the centre. *REQUIRED SKILLS* - enrolled in a PhD or research master programme, in the topic of NLP, speech processing or applied machine learning - experience in at least one of machine translation, ASR or multi-task learning - good knowledge in tensorflow or (preferably) pytorch - track record of published papers in top-tier conferences is a plus *REFERENCES* [1] Tang, Yun, et al. "Improving speech translation by understanding and learning from the auxiliary text translation task." arXiv preprint arXiv:2107.05782 (2021). [2] Li, Xian, et al. "Multilingual speech translation with efficient finetuning of pretrained models." arXiv preprint arXiv:2010.12829 (2020). [3] B?rard, Alexandre, et al. "Listen and translate: A proof of concept for end-to-end speech-to-text translation." arXiv preprint arXiv:1612.01744 (2016). [4] ?st?n, Ahmet, et al. "Multilingual unsupervised neural machine translation with denoising adapters." arXiv preprint arXiv:2110.10472 (2021). https://europe.naverlabs.com/job/using-monolingual-speech-data-to-improve-multilingual-translation-models-internship/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From likforman at telecom-paristech.fr Wed Dec 1 04:11:47 2021 From: likforman at telecom-paristech.fr (Laurence Likforman) Date: Wed, 1 Dec 2021 10:11:47 +0100 Subject: Connectionists: ICPR 2022 Montreal - Call for Workshop Proposals Message-ID: Apologies for multiple copies.... ----------------------------------------- ICPR 2022 - Call for Workshop Proposals ----------------------------------------- The ICPR 2022 Workshop Chairs invite proposals for the 26th International Conference on Pattern Recognition which is to be held in? Montr?al, Qu?bec (QC), Canada during August 21-25, 2022. https://www.icpr2022.com/ Workshops can be half- or full-day, and it is also possible to hold workshops that will be operated in a virtual format but it is expected that most workshops will take place at the same venue as the main conference. We seek Workshops on timely topics and applications of Computer Vision, Image and Sound Analysis, Pattern Recognition and Artificial Intelligence. Workshops are expected to provide a forum for the active exchange of ideas and experiences. Members from all segments of the ICPR community are invited to submit workshop proposals for review. Each proposal will be assessed for its scientific content, proposed structure and overall relevance. Workshop organizers will be responsible for inviting speakers and ensuring their participation, submission and review of papers, and structuring leading discussion sessions. --------------------------------------------------------- Guideline for submitting proposals SEE ATTACHED PDF FILE --------------------------------------------------------- The workshop proposal should be submitted via email to the ICPR 2022 Workshop Chairs at workshops at icpr2022.com by January 17th, 2022 (11:59PM Pacific Time). You will receive an acknowledgement of receipt by email within a few working days. --------------- Important Dates --------------- Workshop proposals due??????????????? January 17, 2022 Workshop proposal decisions??????????? February 14, 2022 Recommended workshop paper deadline??? June 6, 2022 Early bird registration deadline??????????? June 6, 2022 Conference??????????????????????? August 21-25, 2022 Tutorials/Workshops???????????????? August 21, 2022 --------------- Contacts --------------- ICPR 2022 Workshop Co-Chairs, Jonathan Wu (Canada) - jwu at uwindsor.ca Laurence Likforman (France) - likforman at telecom-paristech.fr Giovanni Maria Farinella (Italy) - gfarinella at dmi.unict.it Xiang Bai (China) - xbai at hust.edu.cn -------------- next part -------------- A non-text attachment was scrubbed... Name: 2021-07-14-ICPR-2022-Call-for-workshops.pdf Type: application/pdf Size: 310576 bytes Desc: not available URL: From hongzhi.kuai at gmail.com Wed Dec 1 03:53:34 2021 From: hongzhi.kuai at gmail.com (H.Z. Kuai) Date: Wed, 1 Dec 2021 17:53:34 +0900 Subject: Connectionists: Call for Papers: Brain Informatics 2022 Message-ID: +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ CALL FOR PAPERS The 15th International Conference on Brain Informatics (BI'22) July 15-17, 2022 A Hybrid Conference with both Online and Offline Modes Co-hosted by University of Padua & University of Queensland Padova, Italy (In-Person) & Queensland, Australia (Online) Homepage: wi-consortium.org/conferences/bi2022/ The key theme: Brain Science meets Artificial Intelligence Celebrating the University of Padua's 800 years birthday +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *** IMPORTANT DATES *** - January 15, 2022: Workshop/Special Session proposal deadline - February 28, 2022: Paper submission deadline - March 15, 2022: Abstract submission deadline The International Conference on Brain Informatics (BI) series has established itself as the world's premier research conference on Brain Informatics, which is an emerging interdisciplinary and multidisciplinary research field that combines the efforts of Cognitive Science, Neuroscience, Machine Learning, Data Science, Artificial Intelligence (AI), and Information and Communication Technology (ICT) to explore the main problems that lie in the interplay between human brain studies and informatics research. The 15th International Conference on Brain Informatics (BI'22) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on Brain Informatics research, brain-inspired technologies and brain/mental health applications. *** Topics and Areas *** The key theme of the conference is "Brain Science meets Artificial Intelligence". The BI'22 solicits high-quality original research and application papers (both full paper and abstract submissions). Relevant topics include but are not limited to: Track 1: Cognitive and Computational Foundations of Brain Science Track 2: Human Information Processing Systems Track 3: Brain Big Data Analytics, Curation and Management Track 4: Informatics Paradigms for Brain and Mental Health Research Track 5: Brain-Machine Intelligence and Brain-Inspired Computing *** Paper Submission and Publications *** Paper Submission: ----------------- Full papers should be limited to a maximum of 10 pages including figures and references in Springer LNCS Proceedings format ( https://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines ). Additional pages will be charged. All papers will be peer-reviewed and accepted based on originality, significance of contribution, technical merit, and presentation quality. All papers accepted (and all workshop & special sessions' full-length papers) will be published by Springer as a volume of the Springer-Nature LNAI Brain Informatics Book Series ( https://link.springer.com/conference/brain). Abstract Submission: -------------------- Research abstracts are encouraged and will be accepted for presentations in an oral presentation format and/or poster presentation format. Each abstract submission should include the title of the paper and an abstract body within 500 words. Journal Opportunities: ---------------------- High-quality BI conference papers will be nominated for a fast-track review and publication at the Brain Informatics Journal ( https://braininformatics.springeropen.com/), an international, peer-reviewed, interdisciplinary Open Access journal published by Springer Nature. Special Issues & Books: ----------------------- Workshop/special session organizers and BI conference session chairs may consider and can be invited to prepare a book proposal of special topics for possible book publication in the Springer-Nature Brain Informatics & Health Book Series (https://www.springer.com/series/15148), or a special issue at the Brain Informatics Journal. *** Workshop & Special Sessions *** Proposal Submissions: --------------------- BI'22 will be hosting a series of workshops and special sessions featuring topics relevant to the brain informatics community on the latest research and industry applications. Papers & Presentations: ----------------------- A workshop/special session typically takes a half-day (or full-day) and includes a mix of regular and invited presentations including regular papers, abstracts, invited papers as well as invited presentations. The paper and abstract submissions to workshops/special sessions will follow the same format as the BI conference papers and abstracts. Proposal Guidelines: -------------------- Each proposal should include 1) workshop/special session title; 2) length of the workshop (half/full day); 3) names, main contact, and a short bio of the workshop organizers; 4) brief description of the workshop scope and timeline; 5) prior history of the workshop (if any); 6) potential program committee members and invited speakers; 7) any other relevant information. Publications: ------------- Accepted workshop and special session full papers will be published at the same BI proceedings at the Springer-Nature LNAI Brain Informatics Book Series ( https://link.springer.com/conference/brain). Workshop organizers can be invited to contribute a book publication in the Springer-Nature Brain Informatics & Health Book Series, or a special issue at the Brain Informatics Journal. *** IMPORTANT DATES *** - January 15, 2022: Workshop/Special Session proposal deadline - February 28, 2022: Paper submission deadline - March 15, 2022: Abstract submission deadline - April 15, 2022: Paper acceptance notification - April 20, 2022: Notification of abstract acceptance - April 30, 2022: Final paper and abstract submission deadline - May 5, 2022: Accepted paper and abstract registration deadline - July 15-17, 2022: Conference Contact Us: http://wi-consortium.org/conferences/bi2022/Contact.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From pokornam at cs.cas.cz Wed Dec 1 10:31:06 2021 From: pokornam at cs.cas.cz (Magda Pokorna) Date: Wed, 1 Dec 2021 16:31:06 +0100 Subject: Connectionists: Postdoc / Junior Scientist positions in Prague, Czech Republic In-Reply-To: <734799ed-1216-bbd7-9db3-be68235a2ab1@cs.cas.cz> References: <734799ed-1216-bbd7-9db3-be68235a2ab1@cs.cas.cz> Message-ID: <0a5eb917-065a-91dd-3e6d-c8680ccb6e32@cs.cas.cz> **1. Postdoctoral / Junior Scientist position in complex networks and information theory** is available to join the Complex Networks and Brain Dynamics group for the project: ?Network modelling of complex systems: from correlation graphs to information hypergraphs? funded by the Czech Science Foundation. More information and application at https://www.cs.cas.cz/job-offer/postdoc-junior-position-Hlinka5-2021/en**** **** ** 2. Postdoctoral / Junior Scientist position in Multimodal Neuroimaging Machine Learning** is available to join the Complex Networks and Brain Dynamics group for the project: ?Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data? funded by the Czech Health Research Council. More information and application at https://www.cs.cas.cz/job-offer/postdoc-junior-position-Hlinka6-2021/en ** ****** Do not hesitate to contact the principal investigator for informal inquiries concerning the position: Ing. Mgr. Jaroslav Hlinka, Ph.D., hlinka at cs.cas.cz. Institute of Computer Science Czech Academy of Sciences Pod Vodarenskou vezi 2 Prague 8, 182 07, Czech Republic Web: http://cs.cas.cz/hlinka -------------- next part -------------- An HTML attachment was scrubbed... URL: From morrison at fz-juelich.de Wed Dec 1 13:11:12 2021 From: morrison at fz-juelich.de (Abigail Morrison) Date: Wed, 1 Dec 2021 19:11:12 +0100 Subject: Connectionists: Diversity in Research Papers Award - applications by 21.12 Message-ID: Dear colleagues, the Human Brain Project (HBP) launched the (DIRPA), inviting applications for the Best Diversity in Research Papers, i.e. publications that consider diversity traits such as sex, gender, age, ethnicity, etc. in their specific field of research such as neuroscience, AI or robotics. Differentiating variables has been recognised to be relevant from the level of stem cells to the reproduction of biases by AI applications. Considering sex/gender has become a mandatory requirement for Horizon Europe projects (see also ?Gendered Innovations? policy report). The most outstanding papers will 1. be awarded with a certificate of honour. 2. be presented at the heart of a webinar to a large audience in a dedicated online event organised and promoted by the HBP and EBRAINS, where the authors will discuss their research related to diversity with Lutz J?ncke and further keynote speakers in April 2022. 3. be promoted with a news feature on the HBP and related Web Sites, as well as social media channels with several thousand followers. 4. especially early-stage researchers will receive a voucher for a HBP event of choice. Submission deadline: 21st December 2021 More information & submission: https://www.humanbrainproject.eu/en/about/gender-equality/measures-and-materials/ -- Prof. Dr. Abigail Morrison IAS-6 / INM-6 / SimLab Neuroscience J?lich Research Center & Computer Science 3 - Software Engineering RWTH Aachen http://www.fz-juelich.de/inm/inm-6 http://www.fz-juelich.de/ias/jsc/slns http://www.se-rwth.de Office: +49 2428 8097504 Fax # : +49 2461 61-9460 Pronouns: she/her ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From pubconference at gmail.com Wed Dec 1 17:56:05 2021 From: pubconference at gmail.com (Pub Conference) Date: Wed, 1 Dec 2021 17:56:05 -0500 Subject: Connectionists: [journals] Call for paper-Neural Computing and Applications, Topical Collection on Interpretation of Deep Learning Message-ID: Neural Computing and Applications Topical Collection on Interpretation of Deep Learning: Prediction, Representation, Modeling and Utilization https://www.springer.com/journal/521/updates/19187658 Aims, Scope and Objective While Big Data offers the great potential for revolutionizing all aspects of our society, harvesting of valuable knowledge from Big Data is an extremely challenging task. The large scale and rapidly growing information hidden in the unprecedented volumes of non-traditional data requires the development of decision-making algorithms. Recent successes in machine learning, particularly deep learning, has led to breakthroughs in real-world applications such as autonomous driving, healthcare, cybersecurity, speech and image recognition, personalized news feeds, and financial markets. While these models may provide the state-of-the-art and impressive prediction accuracies, they usually offer little insight into the inner workings of the model and how a decision is made. The decision-makers cannot obtain human-intelligible explanations for the decisions of models, which impede the applications in mission-critical areas. This situation is even severely worse in complex data analytics. It is, therefore, imperative to develop explainable computation intelligent learning models with excellent predictive accuracy to provide safe, reliable, and scientific basis for determination. Numerous recent works have presented various endeavors on this issue but left many important questions unresolved. The first challenging problem is how to construct self-explanatory models or how to improve the explicit understanding and explainability of a model without the loss of accuracy. In addition, high dimensional or ultra-high dimensional data are common in large and complex data analytics. In these cases, the construction of interpretable model becomes quite difficult and complex. Further, how to evaluate and quantify the explainability of a model is lack of consistent and clear description. Moreover, auditable, repeatable, and reliable process of the computational models is crucial to decision-makers. For example, decision-makers need explicit explanation and analysis of the intermediate features produced in a model, thus the interpretation of intermediate processes is requisite. Subsequently, the problem of efficient optimization exists in explainable computational intelligent models. These raise many essential issues on how to develop explainable data analytics in computational intelligence. This Topical Collection aims to bring together original research articles and review articles that will present the latest theoretical and technical advancements of machine and deep learning models. We hope that this Topical Collection will: 1) improve the understanding and explainability of machine learning and deep neural networks; 2) enhance the mathematical foundation of deep neural networks; and 3) increase the computational efficiency and stability of the machine and deep learning training process with new algorithms that will scale. Potential topics include but are not limited to the following: - Interpretability of deep learning models - Quantifying or visualizing the interpretability of deep neural networks - Neural networks, fuzzy logic, and evolutionary based interpretable control systems - Supervised, unsupervised, and reinforcement learning - Extracting understanding from large-scale and heterogeneous data - Dimensionality reduction of large scale and complex data and sparse modeling - Stability improvement of deep neural network optimization - Optimization methods for deep learning - Privacy preserving machine learning (e.g., federated machine learning, learning over encrypted data) - Novel deep learning approaches in the applications of image/signal processing, business intelligence, games, healthcare, bioinformatics, and security Guest Editors Nian Zhang (Lead Guest Editor), University of the District of Columbia, Washington, DC, USA, nzhang at udc.edu Jian Wang, China University of Petroleum (East China), Qingdao, China, wangjiannl at upc.edu.cn Leszek Rutkowski, Czestochowa University of Technology, Poland, leszek.rutkowski at pcz.pl Important Dates Deadline for Submissions: March 31, 2022 First Review Decision: May 31, 2022 Revisions Due: June 30, 2022 Deadline for 2nd Review: July 31, 2022 Final Decisions: August 31, 2022 Final Manuscript: September 30, 2022 Peer Review Process All the papers will go through peer review, and will be reviewed by at least three reviewers. A thorough check will be completed, and the guest editors will check any significant similarity between the manuscript under consideration and any published paper or submitted manuscripts of which they are aware. In such case, the article will be directly rejected without proceeding further. Guest editors will make all reasonable effort to receive the reviewer?s comments and recommendation on time. The submitted papers must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue (with at least 30% difference from the original works). Submission Guidelines Paper submissions for the special issue should strictly follow the submission format and guidelines ( https://www.springer.com/journal/521/submission-guidelines ). Each manuscript should not exceed 16 pages in length (inclusive of figures and tables). Manuscripts must be submitted to the journal online system at https://www.editorialmanager.com/ncaa/default.aspx . Authors should select ?TC: Interpretation of Deep Learning? during the submission step ?Additional Information?. -------------- next part -------------- An HTML attachment was scrubbed... URL: From likforman at telecom-paristech.fr Thu Dec 2 05:55:12 2021 From: likforman at telecom-paristech.fr (Laurence Likforman) Date: Thu, 2 Dec 2021 11:55:12 +0100 Subject: Connectionists: Call for Papers ICPRAI 2022 Paris (France) In-Reply-To: References: Message-ID: <00fd23ff-f7f2-062c-b078-febf2c0f72cd@telecom-paristech.fr> *CALL for Papers ICPRAI 2022* *Endorsed by IAPR* Deadline for Paper submission: 15/12/2021 Printed in LNCS proceedings volume ** You are invited to submit a paper for the third International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2022) It will be held in Paris, France, 1-3 June 2022 See at https://icprai2022.sciencesconf.org At the moment in Paris (France), we cannot predict what will be?sanitary situation next June.?In this context, we cannot schedule for sure, how the conference will take place. We hope most of you can travel for an on site conference, but an hybrid version is also possible. *Scope of the Conference* The conference aims to bring together researchers, students and practitioners of pattern recognition and artificial intelligence, to present and discuss new advances. *Pattern recognition*: recognition of different types of patterns, feature extraction / selection and evaluation, structural / statistical approaches *Computer vision*: image processing / analysis, segmentation, object recognition, scene understanding *Artificial intelligence*: machine / deep learning, expert systems, system interpretability, knowledge representation, perception, semantic analysis, intelligent systems *Big data*: data visualization, volume / velocity / data variety, small sample size, supercomputing, cloud, data mining and performance evaluation *With applications *related to: handwriting, document, text, language processing, e-learning, image processing / analysis, bio-medical imaging, remote sensing, image retrieval, 2D / 3D images and graphics, audio / video, multimedia applications, security and forensic studies, mobile applications, face, fingerprint, iris, brain, strategic objects and targets, industrial applications of PRAI, innovation and technology transfer, financial trends and analysis, traffic analysis and smart transportation systems, robotics and autonomous vehicles ... With 5 *special sessions* ?Medical Applications of Pattern Recognition and AI ?Analysis and learning of multi-variate, multi-temporal, multi-resolution and multi-source remote sensing data ?Graphs for Pattern Recognition: Representations, Theory and Applications ?Time series analysis ?Vis&ML for XAI:?Bridging the gap between ML and visualization communities for eXplainable Artificial Intelligence and *3 keynotes* A *Special Issue* is scheduled for the best papers in IJPRAI journal As well as a *Special Section* of the Pattern Recognition Letters ?(Elsevier) journal. *Proposed by:* Honorary Chair Ching Y. Suen (Canada) General chair Nicole Vincent (France) Conference Co-Chairs Edwin Hancock (UK) Yuan Y. Tang (China) Program Chairs Mounim El Yacoubi (France) Umapada Pal (India) Eric Granger (Canada) Pong C. Yuen (China) *Key dates* Deadline for Paper submission: 15/12/2021 Author notification: 8/03/2022 ** *Submissions* The conference solicits papers covering any of these topics. Papers will be 12 pages of content in the Springer LNCS style and should report on novel, unpublished work. The proceedings of the conference will be published as a Lecture Notes in Computer Science (LNCS) proceedings volume. *Contact* icprai2022 at sciencesconf.org Sponsors are : IMDS , IDEMIA , LIPADE , Universit? de Paris facult? des Sciences From ahtan at smu.edu.sg Thu Dec 2 22:59:28 2021 From: ahtan at smu.edu.sg (TAN Ah Hwee) Date: Fri, 3 Dec 2021 03:59:28 +0000 Subject: Connectionists: Multiple Research Positions And PhD Scholarships Available at School of Computing and Information Systems, Singapore Management University In-Reply-To: <4bfd76c1c2524dc99cd412fdad7067f9@smu.edu.sg> References: <4bfd76c1c2524dc99cd412fdad7067f9@smu.edu.sg> Message-ID: <6c18692817a04be2b7882ad5254adbc2@smu.edu.sg> Dear Connectionists The Neural and Cognitive Computing group at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU) is looking to fill a number of fully funded research positions, including Postdoctoral Research Fellows, Research Associates/Engineers and Postgraduate Students. Members in the group have been working on computational principles and modelling of neural and cognitive functions, including perception, learning, memory, language, reasoning, decision making, and self-awareness. Our research is funded through competitive grants from multiple public agencies and industry sector, and we are running several externally funded projects, involving modelling and learning of domain knowledge from text documents, large scale simulation of adaptive Computer Generated Forces (CGF) and trustworthy federated learning etc. Successful candidate will join an active research team led by Ah-Hwee TAN, Zhaoxia WANG, and Budhitama SUBAGDJA. The group is part of the vibrant collaborative research network in Singapore and collaborates closely with Nanyang Technological University (NTU), Agency for Science, Technology and Research (A*STAR) and DSO National Laboratories. Visit our homepage for more details at https://sites.google.com/smu.edu.sg/cognitiveandneuralcomputing/home. About the Postdoctoral Research Fellow position: The main scope of work of the postdoctoral fellow position include: a) Research and development of computational models for multi-agent reinforcement learning and trustworthy federated Learning; b) Leading the design, development and evaluation of simulation prototypes; and c) Documentation, preparation of technical publications and reports Academic / Professional Qualifications ? PhD degree in Computer Science, Cognitive Science, or closely related disciplines from a reputable institution of higher learning ? Minimum 3-4 years of relevant research experience in artificial intelligence, cognitive science, or related fields. Knowledge / Skills / Competencies ? Good analytical, technical and problem solving skills ? Knowledge/Proficiency in programming languages, in particular Python and Java ? Competency in application prototype design and development ? Good writing, communication and interpersonal skills ? Applicants with research publications in artificial intelligence and cognitive science areas will be advantageous About the Research Associate/Engineer position The main responsibilities of the research associate/engineer position include: a) Study, design, development and integration of computational models for knowledge representation, association and reasoning b) Responsible for the design and development of application prototype for demonstration c) Documentation, preparation of technical publications and reports Academic / Professional Qualifications ? BSc/Master degree in Computer Science, Information Technology, Information Systems or closely related disciplines from a reputable institution of higher learning ? Minimum 1-2 years of relevant research experience in artificial intelligence, cognitive science, or related fields will be an advantage. Knowledge / Skills / Competencies ? Good analytical, technical and problem solving skills ? Knowledge/Proficiency in programming languages, in particular Python, Java and C/C++ ? Competency in application prototype design and development ? Good writing, communication and interpersonal skills ? Applicants with research publications in artificial intelligence and cognitive science areas will be advantageous The appointment will typically be for one year initially and renewable for multiple years. The salary and benefits provided will be highly competitive and commensurate with the candidate?s profile and experience. We also welcome candidates who are keen to pursue a PhD in the field of AI, machine learning, neural networks, and cognitive computing. Fully funded scholarships with stipends are available. Visiting students and researchers are also encouraged to contact us to discuss opportunities. Interested candidate please send a cover letter and CV with email addresses of three referees to ahtan at smu.edu.sg . Your email should have the subject heading of "Application for Research Position? or ?Application for Postgraduate Study". We are looking to fill the positions as early as possible. Reviews of applications will begin immediately and continue until all positions are filled. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 4925 bytes Desc: not available URL: From rpaudel142 at gmail.com Thu Dec 2 14:03:29 2021 From: rpaudel142 at gmail.com (Ramesh Paudel) Date: Thu, 2 Dec 2021 14:03:29 -0500 Subject: Connectionists: CFP Reminders - (SaT-CPS 2022) ACM Workshop on Secure and Trustworthy Cyber-Physical Systems Message-ID: Dear Colleagues, *** Please accept our apologies if you receive multiple copies of this CFP *** Please consider submitting and/or forwarding to the appropriate groups/personnel the opportunity to submit to the ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (SaT-CPS 2022), which will be held in Baltimore-Washington DC area (or virtually) on April 26, 2022 in conjunction with the 12th ACM Conference on Data and Application Security and Privacy (CODASPY 2022). *** Paper submission deadline: December 30, 2021 *** *** Website: https://sites.google.com/view/sat-cps-2022/ *** SaT-CPS aims to represent a forum for researchers and practitioners from industry and academia interested in various areas of CPS security. SaT-CPS seeks novel submissions describing practical and theoretical solutions for cyber security challenges in CPS. Submissions can be from different application domains in CPS. Example topics of interest are given below, but are not limited to: Secure CPS architectures - Authentication mechanisms for CPS - Access control for CPS - Key management in CPS - Attack detection for CPS - Threat modeling for CPS - Forensics for CPS - Intrusion and anomaly detection for CPS - Trusted-computing in CPS - Energy-efficient and secure CPS - Availability, recovery, and auditing for CPS - Distributed secure solutions for CPS - Metrics and risk assessment approaches - Privacy and trust - Blockchain for CPS security - Data security and privacy for CPS - Digital twins for CPS - Wireless sensor network security - CPS/IoT malware analysis - CPS/IoT firmware analysis - Economics of security and privacy - Securing CPS in medical devices/systems - Securing CPS in civil engineering systems/devices - Physical layer security for CPS - Security on heterogeneous CPS - Securing CPS in automotive systems - Securing CPS in aerospace systems - Usability security and privacy of CPS - Secure protocol design in CPS - Vulnerability analysis of CPS - Anonymization in CPS - Embedded systems security - Formal security methods in CPS - Industrial control system security - Securing Internet-of-Things - Securing smart agriculture and related domains The workshop is planned for one day, April 26, 2022, on the last day of the conference. Instructions for Paper Authors All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal. All papers must be submitted electronically via the Easychair system: https://easychair.org/conferences/?conf=acmsatcps2022 Full-length papers Papers must be at most 10 pages in length in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template). Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM Digital Library. The presenter must register for the workshop before the deadline for author registration. Position papers and Work-in-progress papers We also invite short position papers and work-in-progress papers. Such papers can be of length up to 6 pages in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template), and must clearly state "Position Paper" or "Work in progress," as the case may be in the title section of the paper. These papers will be reviewed and accepted papers will be published in the conference proceedings. Important Dates Due date for full workshop submissions: December 30, 2021 Notification of acceptance to authors: February 10, 2022 Camera-ready of accepted papers: February 20, 2022 Workshop day: April 26, 2022 *- - - - - - - - - - -* *Ramesh Paudel, Ph.D.* Publicity and Web Co-Chair Research Scientist George Washington University Washington, DC. -------------- next part -------------- An HTML attachment was scrubbed... URL: From michael.schaub at rwth-aachen.de Thu Dec 2 05:25:54 2021 From: michael.schaub at rwth-aachen.de (Michael Schaub) Date: Thu, 2 Dec 2021 11:25:54 +0100 Subject: Connectionists: PhD positions at RWTH Aachen University, Germany Message-ID: ====================================================================== Various Open Positions for Doctoral Researchers in the post-graduate program UnRAVeL ?Uncertainty and Randomness in Algorithms, Verification and Logic? at RWTH Aachen University, Aachen, Germany https://www.unravel.rwth-aachen.de/ ====================================================================== Context. RWTH Aachen University is looking for enthusiastic and highly qualified doctoral researchers. Various positions are available within the interdisciplinary Research Training Group (RTG) UnRAVeL founded by German Research Foundation (DFG). The key emphasis of an RTG is on the qualification of doctoral researchers with a focused research program and a structured training strategy. The RTG UnRAVeL aims to significantly advance probabilistic modelling and analysis for uncertainty by developing new theories, algorithms, and tool-supported verification techniques, and to apply them to core problems from application areas such as: applied machine learning (in control theory as well as network and data science), planning in AI (e.g., robotics), as well as safety and performance analysis (railway systems). Within UnRAVeL, theoretical computer scientists from computer-aided verification, automata and logic, algorithms and complexity, together with experts from management science (robust optimization), applied computer science (network and data science), mechanical and railway engineering intensively cooperate. UnRAVeL PIs are: Erika Abraham, Christina B?sing, J?rgen Giesl, Martin Grohe, Joost-Pieter Katoen, Gerhard Lakemeyer, Christof L?ding, Nils Niessen, Britta Peis, Sebastian Trimpe, Michael Schaub, and Gerhard Woeginger. Current and completed doctoral UnRAVeL projects can be found here: https://www.unravel.rwth-aachen.de/cms/UnRAVeL/Forschung/~ofhi/Dissertationsprojekte/?lidx=1 Required profile. Candidates must have (or soon obtain) a master degree in Computer Science, Mathematics or related area and have completed their studies with excellent grades. You should have interest in performing original, highly competitive scientific research, publishing your results in top conferences and scientific journals. Self-motivation and the ability to work both independently and as a team player in local and international research groups are expected. Fluency in English is required; proficiency in German is helpful but not compulsory. How to apply? Your written application should contain: - a curriculum vitae - a transcript of records (list of courses and grades) - a cover letter including a statement of interest in (some of) the ? RTG topics, and - a recommendation letter e.g., by your master thesis supervisor(s) All documents should be formatted as a single pdf-file. The recommendation letter can provided separately, if needed. You should send your application ultimately by ** December 20, 2021 (AoE) ** to the e-mail address: unravel-appl at cs.rwth-aachen.de. We check applications once they are received, and will conduct interviews until our vacancies are filled. What do we offer? We offer a stimulating international research environment, the possibility to participate in highly competitive and interdisciplinary research and the opportunity to involve students in your research through project work.? Doctoral researchers have a status as employee with a salary according to the German federal employee scale TV-L E13; the exact salary is subject to your family situation. The duration of the positions is three years with a possible extension to four years. RWTH Aachen University offers excellent facilities for professional and personal development.? Starting date of the positions: 2022 (flexible). Enquiries can be directed to Prof. Joost-Pieter Katoen (e-mail: katoen at cs.rwth-aachen.de). RWTH Aachen University is certified as a ?Family-Friendly University?. We particularly welcome and encourage applications from women, disabled persons and ethnic minority groups, recognizing they are underrepresented across RWTH Aachen University. The principles of fair and open competition apply and appointments will be made on merit. From mtista at gmail.com Thu Dec 2 18:24:04 2021 From: mtista at gmail.com (Massimo Tistarelli) Date: Fri, 3 Dec 2021 00:24:04 +0100 Subject: Connectionists: Call for Applications: 19th Int.l Summer School on Biometrics 2022 Message-ID: ?? Please accept our sincere apologies for receiving multiple copies of this announcement ?? ** * * *19^th Int.l Summer School for Advanced Studies on Biometrics for Secure Authentication:* * * ***CONTINUALLY LEARNING BIOMETRICS* * * *Alghero, Italy? ?? June 6 - 10 2022* http://biometrics.uniss.it *** * ** To face the expected travel limitations due to the Covid-19 outbreak, the school is planned as a mixed virtual event, allowing participation both in person and remotely with videoconference facilities *Contact:*tista at uniss.it ** ** *** * *Application deadline: FEBRUARY 15**^th 2022 *(download the application form at: http://biometrics.uniss.it ) From the early days, when security was the driving force behind biometric research, today?s challenges go far beyond security. Machine learning, Image understanding, Signal analysis, Neuroscience, Robotics, Forensic science, Digital forensics and other disciplines, converged in a truly multidisciplinary effort to devise and build advanced systems to facilitate the interpretation of signals recorded from individuals acting in a given environment. This is what we simply call today ?Biometrics?. For the last nineteen years, the International Summer School on Biometrics has been closely following the developments in science and technology to offer a cutting edge, intensive training course, always up to date with the current state-of-the-art. What are the most up-to-date core biometric technologies developed in the field? What is the potential impact of biometrics in forensic investigation and crime prevention? What can we learn from human perception? How to deploy current Machine Learning approaches? How to deal with /adversarial attacks/ in biometric recognition? How can a biometric system learn continually? This school follows the successful track of the International Summer Schools on Biometrics held since 2003. In this 19^th edition, the courses will mainly focus on new and emerging issues: ? *The impact of AI and advanced learning techniques in Biometrics;* ? *How to make ?Deep Biometrics? systems /explainable/;* ? *The advantages of continual learning for biometrics;* ? *How to exploit new biometric technologies in forensic and emerging applications.* The courses will provide a clear and in-depth picture on the state-of-the-art in biometric verification/identification technology, both under the theoretical and scientific point of view as well as in diverse application domains. The lectures will be given by 18 outstanding experts in the field, from both academia and industry. An advanced feature of this summer school will be some practical sessions to better understand, ?hands on?, the real potential of today?s biometric technologies. *Participant application*** The expected school fees will be in the order of 1,600 ? (400 ? in videoconference) for students and 2,200 ? (800 ? in videoconference) for others. The fees will include full board accommodation, all courses and handling material. A limited number of scholarships, partially covering the fees, will be awarded to Phd students, selected on the basis of their scientific background and on-going research work. The scholarship request form can be downloaded from the school web site http://biometrics.uniss.it Send a filled application form (download from http://biometrics.uniss.it) together with a short resume to: *Prof. Massimo Tistarelli ?*e-mail: *biometricsummerschool at gmail.com* * Submission of applications: February 15th, 2022 * Notification of acceptance: March 20th, 2022 * Registration: April 25th, 2022 *_Advance pre-registration is strictly required by February 15^th 2022_* *School location* The school will be hosted by Hotel Dei Pini (https://www.hoteldeipini.com/ ) in the Capo Caccia bay, near Alghero, Sardinia. This is one of the most beautiful resorts in the Mediterranean Sea. The structure is beautifully immersed into the Capo Caccia bay. The hotel Dei Pini has a recently renovated conference centre, fully equipped for scientific events. The school venue, as well as the surroundings, proved to be a perfect environment for the school activities.** The school lectures will be delivered as a *mixed mode event*, allowing both physical (if the medical advice at the time of the school will allow it in full security) and remote attendance with videoconferencing facilities. * For participants attending in videoconference, live lectures will be delivered online with full sharing of the lecturing material and allowing live interaction with the participants. Private and group meetings with each lecturer will be organised to deepen the discussion started in the class. * Ad-hoc teleconferencing and communication tools will be also set up for practical hands-on sessions and to allow a good engagement of the participants and the lecturers. * Open sessions will be organised with questions and answers moderated by the leading experts in the field. The organisers and all lecturers are fully committed to make this year's school as successful, instructing and inspiring as in the past years. *School Committee:*** * * *Massimo Tistarelli* Computer Vision Laboratory ? University of Sassari, Italy *Josef Bigun * Department of Computer Science ? Halmstad University, Sweden *Enrico Grosso* Computer Vision Laboratory ? University of Sassari, Italy *Anil K. Jain* Biometrics laboratory ? Michigan State University, USA * * *Distinguished lecturers from past school editions*** *Josef **Bigun* Halmstad University ? Sweden *David Meuwly* Netherlands Forensic Institute ? NL *Thirimachos Bourlai* West Virginia University ? USA *Emilio Mordini MD* Responsible Technologies ? Italy *Vincent Bouatou* Safran Morpho ? France *Mark Nixon* University of Southampton ? UK *Kevin Bowyer * University of Notre Dame ? USA *Alice O?Toole* University of Texas ? USA *Deepak Chandra * Google Inc. ? USA *Maja Pantic* Imperial College ? UK *Rama Chellappa* University of Maryland ? USA *Johnathon Phillips* NIST ? USA *John Daugman* University of Cambridge ? UK *Tomaso Poggio* MIT ? USA *Farzin Deravi* University of Kent ? UK *Nalini Ratha* IBM ? USA *James Haxby* Dartmouth University ? USA *Arun Ross* Michigan State University ? USA** *Anil K. Jain* Michigan State University ? USA *Tieniu Tan * CASIA-NLPR ? China *Joseph Kittler* University of Surrey ? UK *Massimo Tistarelli* Universit? di Sassari ? Italy *Davide Maltoni* Universit? di Bologna ? Italy *Alessandro Verri* Universit? di Genova ? Italy *John Mason* Swansea University ? UK *James Wayman* University of San Jos? ? USA *Aldo Mattei* Arma dei Carabinieri ? Italy *Lior Wolf* Tel Aviv University ? Israel -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Wed Dec 1 16:14:58 2021 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Wed, 1 Dec 2021 21:14:58 +0000 Subject: Connectionists: NEURAL NETWORKS, Dec. 2021 Message-ID: Neural Networks - Volume 144, December 2021 https://www.journals.elsevier.com/neural-networks Adversarial text-to-image synthesis: A review Stanislav Frolov, Tobias Hinz, Federico Raue, Joern Hees, Andreas Dengel Biologically motivated learning method for deep neural networks using hierarchical competitive learning Takashi Shinozaki The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain Hiroshi Yamakawa Impact of axonal delay on structure development in a multi-layered network Catherine E. Davey, David B. Grayden, Anthony N. Burkitt Active inference through whiskers Francesco Mannella, Federico Maggiore, Manuel Baltieri, Giovanni Pezzulo An end-to-end 3D convolutional neural network for decoding attentive mental state Yangsong Zhang, Huan Cai, Li Nie, Peng Xu, ... Cuntai Guan Predictive coding feedback results in perceived illusory contours in a recurrent neural network Zhaoyang Pang, Callum Biggs O'May, Bhavin Choksi, Rufin VanRullen Performance of biologically grounded models of the early visual system on standard object recognition tasks Michael Teichmann, Rene Larisch, Fred H. Hamker Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control Tom Macpherson, Masayuki Matsumoto, Hiroaki Gomi, Jun Morimoto, ... Takatoshi Hikida Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research Tom Macpherson, Anne Churchland, Terry Sejnowski, James DiCarlo, ... Takatoshi Hikida Weak sub-network pruning for strong and efficient neural networks Qingbei Guo, Xiao-Jun Wu, Josef Kittler, Zhiquan Feng Extreme neural machines Megan Boucher-Routhier, Bill Ling Feng Zhang, Jean-Philippe Thivierge P-DIFF+: Improving learning classifier with noisy labels by Noisy Negative Learning loss QiHao Zhao, Wei Hu, Yangyu Huang, Fan Zhang Learning lightweight super-resolution networks with weight pruning Xinrui Jiang, Nannan Wang, Jingwei Xin, Xiaobo Xia, ... Xinbo Gao Distributed associative memory network with memory refreshing loss Taewon Park, Inchul Choi, Minho Lee Schematic memory persistence and transience for efficient and robust continual learning Yuyang Gao, Giorgio A. Ascoli, Liang Zhao Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems Shunchao Zhang, Bo Zhao, Derong Liu, Yongwei Zhang Extremely randomized neural networks for constructing prediction intervals Tullio Mancini, Hector Calvo-Pardo, Jose Olmo Forward and inverse reinforcement learning sharing network weights and hyperparameters Eiji Uchibe, Kenji Doya Adversarial parameter defense by multi-step risk minimization Zhiyuan Zhang, Ruixuan Luo, Xuancheng Ren, Qi Su, ... Xu Sun Neural-network-based discounted optimal control via an integrated value iteration with accuracy guarantee Mingming Ha, Ding Wang, Derong Liu An empirical evaluation of active inference in multi-armed bandits Dimitrije Markovic, Hrvoje Stojic, Sarah Schwoebel, Stefan J. Kiebel Incremental multi-view spectral clustering with sparse and connected graph learning Hongwei Yin, Wenjun Hu, Zhao Zhang, Jungang Lou, Minmin Miao Recurrent neural network from adder's perspective: Carry-lookahead RNN Haowei Jiang, Feiwei Qin, Jin Cao, Yong Peng, Yanli Shao Nonlinear tensor train format for deep neural network compression Dingheng Wang, Guangshe Zhao, Hengnu Chen, Zhexian Liu, ... Guoqi Li Neural network surgery: Combining training with topology optimization Elisabeth J. Schiessler, Roland C. Aydin, Kevin Linka, Christian J. Cyron Uncertainty propagation for dropout-based Bayesian neural networks Yuki Mae, Wataru Kumagai, Takafumi Kanamori Structured Ensembles: An approach to reduce the memory footprint of ensemble methods Jary Pomponi, Simone Scardapane, Aurelio Uncini Broad-UNet: Multi-scale feature learning for nowcasting tasks Jesus Garcia Fernandez, Siamak Mehrkanoon Combination of certainty and uncertainty: Using FusionGAN to create abstract paintings Mao Li, Jiancheng Lv, Chenwei Tang, Jian Wang, ... Youcheng Huang Combining STDP and binary networks for reinforcement learning from images and sparse rewards Sergio F. Chevtchenko, Teresa B. Ludermir Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia Maryam Doborjeh, Zohreh Doborjeh, Alexander Merkin, Helena Bahrami, ... Nikola Kasabov A conversational model for eliciting new chatting topics in open-domain conversation Weizhao Li, Feng Ge, Yi Cai, Da Ren World model learning and inference Karl Friston, Rosalyn J. Moran, Yukie Nagai, Tadahiro Taniguchi, ... Josh Tenenbaum The generalized extreme learning machines: Tuning hyperparameters and limiting approach for the Moore-Penrose generalized inverse Meejoung Kim A language modeling-like approach to sketching Lisa Graziani, Marco Gori, Stefano Melacci Deep-Hook: A trusted deep learning-based framework for unknown malware detection and classification in Linux cloud environments Tom Landman, Nir Nissim Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning Malte Schilling, Andrew Melnik, Frank W. Ohl, Helge J. Ritter, Barbara Hammer ARAE: Adversarially robust training of autoencoders improves novelty detection Mohammadreza Salehi, Atrin Arya, Barbod Pajoum, Mohammad Otoofi, ... Hamid R. Rabiee A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer Hailiang Ye, Yi Wang, Feilong Cao TACN: A Topical Adversarial Capsule Network for textual network embedding Xiaorui Qin, Yanghui Rao, Haoran Xie, Jiahai Wang, Fu Lee Wang Intermittent control for finite-time synchronization of fractional-order complex networks Lingzhong Zhang, Jie Zhong, Jianquan Lu TGAN: A simple model update strategy for visual tracking via template-guidance attention network Kai Yang, Haijun Zhang, Dongliang Zhou, Linlin Liu Non-differentiable saddle points and sub-optimal local minima exist for deep ReLU networks Bo Liu, Zhaoying Liu, Ting Zhang, Tongtong Yuan A neural decoding algorithm that generates language from visual activity evoked by natural images Wei Huang, Hongmei Yan, Kaiwen Cheng, Chong Wang, ... Huafu Chen Bipartite synchronization of signed networks via aperiodically intermittent control based on discrete-time state observations Dongsheng Xu, Jiahuan Pang, Huan Su Pinning multisynchronization of delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations Libiao Peng, Xifeng Li, Dongjie Bi, Xuan Xie, Yongle Xie A note on computing with Kolmogorov Superpositions without iterations Robert Demb, David Sprecher Highly parallelized memristive binary neural network Jiadong Chen, Shiping Wen, Kaibo Shi, Yin Yang Theory of deep convolutional neural networks III: Approximating radial functions Tong Mao, Zhongjie Shi, Ding-Xuan Zhou One-stage CNN detector-based benthonic organisms detection with limited training dataset Tingkai Chen, Ning Wang, Rongfeng Wang, Hong Zhao, Guichen Zhang Deep Tobit networks: A novel machine learning approach to microeconometrics Jiaming Zhang, Zhanfeng Li, Xinyuan Song, Hanwen Ning Working Memory Connections for LSTM Federico Landi, Lorenzo Baraldi, Marcella Cornia, Rita Cucchiara Deep learning based spectral CT imaging Weiwen Wu, Dianlin Hu, Chuang Niu, Lieza Vanden Broeke, ... Ge Wang Physics-incorporated convolutional recurrent neural networks for source identification and forecasting of dynamical systems Priyabrata Saha, Saurabh Dash, Saibal Mukhopadhyay Detection of pancreatic cancer by convolutional-neural-network-assisted spontaneous Raman spectroscopy with critical feature visualization Zhongqiang Li, Zheng Li, Qing Chen, Alexandra Ramos, ... Jian Xu ACSL: Adaptive correlation-driven sparsity learning for deep neural network compression Wei He, Meiqing Wu, Siew-Kei Lam Disturbance-immune weight sharing for neural architecture search Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, ... Mingkui Tan Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing Youngeun Kim, Priyadarshini Panda -------------- next part -------------- An HTML attachment was scrubbed... URL: From info at incf.org Thu Dec 2 05:29:54 2021 From: info at incf.org (INCF) Date: Thu, 2 Dec 2021 11:29:54 +0100 Subject: Connectionists: INCF endorses a new FAIR software best practice! Message-ID: *INCF endorses the Five Recommendations for FAIR Software as a Best Practice* The Five Recommendations for FAIR Software aim to encourage the greater adoption of FAIR principles by providing a set of starting recommendations that researchers can use to improve the quality, reach, and reproducibility of their software. The recommendations were created by The Netherlands eScience Center and DANS , the Dutch national centre of expertise and repository for research data. The Five Recommendations for FAIR Software were endorsed on November 30, 2021, after a public comment period and review by the INCF SBP committee. Find their use cases here . Learn more about the recommendations here . [image: fair-soft-endorsed-img.png] /The INCF Secretariat -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fair-soft-endorsed-img.png Type: image/png Size: 72027 bytes Desc: not available URL: From ioannakoroni at csd.auth.gr Fri Dec 3 08:10:44 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Fri, 3 Dec 2021 15:10:44 +0200 Subject: Connectionists: Three Deep learning and Computer Vision Postdoc Positions Jointly Supervised in Aristotle University of Thessaloniki, Greece and Henan University, China References: <006d01d7bc1c$8e5c5180$ab14f480$@csd.auth.gr> <021a01d7e835$d2078d60$7616a820$@csd.auth.gr> <00f201d7e83f$212f2340$638d69c0$@csd.auth.gr> Message-ID: <02c401d7e847$2f049330$8d0db990$@csd.auth.gr> Three Deep learning and Computer Vision Postdoc Positions Jointly Supervised in Aristotle University of Thessaloniki, Greece and Henan University, China Position Description Three postdoctoral positions are immediately available at the Data Science and Artificial Intelligence Team/Lab, Henan University; the postdoc fellows will be co-supervised by Prof. Ioannis Pitas from Aristotle University of Thessaloniki, Greece. The postdoc fellows can stay 4-5 months with Prof. Ioannis Pitas at Aristotle University of Thessaloniki, Greece; but they should stay in China for at least 7-8 months per year. Position Location The postdocs will be paid by Henan University, China. They will stay in Aristotle University of Thessaloniki (4-5 months), Thessaloniki, Greece, and Henan University (7-8 months), Kaifeng, China Subject Areas Deep learning and Computer Vision, including but not limited to Object Detection/Recognition, Region Segmentation and related topics. Salary 1800~2200 EUR net per month. Application Deadline December 31st, 2022 Duration of the contract The duration of the contract is 24~36 months, and can be extended up to 48 months. Salary a) The monthly net income of the Postdoctoral researcher is around 1800~2200 EUR (after taxes being deducted), paid by Henan University. b) Additionally, the University will provide a total amount of 100,000 RMB as the candidate's research funding, which can be used for research purposes such as conferences, traveling, meetings, etc. Note: This research funding is once for all, not per year. Note: The Living expenses in Kaifeng is relatively low. For instance, Accommodation cost (two bedrooms, one living room) in Kaifeng is about 150~200 EUR per month. Food cost in KaiFeng is about 100-150 EUR per month. Requirements/Qualifications 1. The successful candidates should hold a PhD degree in machine learning, or computer vision/pattern recognition, or other related fields. 2. At the time of appointment, the applicants must be no more than 35 years old in age. 3. The applicants should have good publication records in the above-mentioned fields. About Aristotle University of Thessaloniki, Greece Artificial Intelligence and Information Analysis Lab ( https://aiia.csd.auth.gr/) Aristotle at University of Thessaloniki (AUTH) has one the best R&D records in Europe (72+R&D projects, mostly EC funded). The Department of Informatics at AUTH is ranked 1st among the Greek Universities and 106th internationally in the field of Mathematics & Computer Science for 2019 in the Leiden Ranking list, which mainly depends on the scientific impact and staff publications. It is also ranked 1st among the Greek Universities in the international ranking list Guide2Research, for 2021, having 5 faculty members in the list of top scientists in the scientific area of Computer Science and Electronics. Aristotle University of Thessaloniki (AUTH), established in 1925, is among the most prestigious universities in Greece. Its computer science discipline is ranked #335 in the world in the US News University Ranking 2021. Prof. Ioannis Pitas (34100+ citations, h-index 87) is an IEEE Fellow, EURASIP fellow and a world-renowned professor in multimedia systems and computer vision. Homepage: https://aiia.csd.auth.gr/computer-vision-machine-learning/#people https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=en About Henan University and KaiFeng, China Henan University has a history of 109 years, and has been selected as the ''Double First Class'' University by the Ministry of Education of China, see http://en.henu.edu.cn/. KaiFeng is a historical city (capital of Song Dynasty) and a famous tourist destination, see https://en.wikipedia.org/wiki/Kaifeng. How to apply Applications are only accepted via Email. All the following documents should be sent to Prof. Ioannis Pitas and Prof. Chongsheng Zhang simultaneously, at pitas at csd.auth.gr and chongsheng.zhang at yahoo.com, with the email subject ''Postdoc application'': - 1. A cover letter - 2. Full CV and list of publications - 3. Two reference letters. If you have any questions, do not hesitate to contact Prof. Ioannis Pitas and Prof. Chongsheng Zhang via Email. -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From benoit.frenay at unamur.be Mon Dec 6 04:35:44 2021 From: benoit.frenay at unamur.be (=?UTF-8?B?QmVub8OudCBGcsOpbmF5?=) Date: Mon, 6 Dec 2021 10:35:44 +0100 Subject: Connectionists: =?utf-8?q?Job_ing_=C3=A9lectro_projet_SMARTSENS_?= =?utf-8?q?=28IoT_+_ML_=29?= Message-ID: <34e5bcf3-2b70-4b88-f90a-a7de1708481e@unamur.be> Chers coll?gues, Je relaie cette offre d'emploi du CeREF pour un(e) ing?nieur(e) ?lectronicien(nne) dans le cadre du projet de recherche Win2Wal SMARTSENS en partenariat avec VOCSens et mon ?quipe ? l?UNamur. Le (La) candidat(e) s?lectionn?(e) int?grera l??quipe de 8 ing?nieurs chercheurs d?j? en place au CeREF. Le projet SMARTSENS a pour objectif de concevoir un r?seau de mesure IoT innovant, utilisant des micro-capteurs de gaz et int?grant des techniques de Machine Learning pour am?liorer la pr?cision des mesures de qualit? d'air, associ?es au suivi d'?missions industrielles, au contr?le de proc?d?s et ? la s?curit?. L?ing?nieur(e) embauch?(e) aura pour mission de concevoir les dispositifs ?lectroniques, les logiciels embarqu?s et l?infrastructure du r?seau. Un descriptif complet de l'offre est en pi?ce jointe. Cordialement, Beno?t Fr?nay -------------- next part -------------- A non-text attachment was scrubbed... Name: CeREF_OffreEmploi_Mons_Smartsens_12_2021.pdf Type: application/pdf Size: 126162 bytes Desc: not available URL: From anja.meunier at univie.ac.at Mon Dec 6 05:15:23 2021 From: anja.meunier at univie.ac.at (Anja Meunier) Date: Mon, 06 Dec 2021 11:15:23 +0100 Subject: Connectionists: 3rd BCI-UC: Voting open until Sunday Message-ID: Dear colleagues, the voting period for the 3rd BCI Un-Conference is now open! Find the registration and voting portal here [1] [1]. We have received many excellent submissions, now it is your turn to vote for those that you would like to hear about during BCI-UC on January 27th, 2022. The voting portal will be open until Sunday, December 12th, 2021, 11:59 pm (CET). We will invite the authors of the top-voted abstracts to present at the un-conference. In addition, the 3rd BCI-UC will feature keynotes by Cynthia Chestek (University of Michigan) [2] and Thorsten Zander (TU Brandenburg) [3]. BCI-UC is an online un-conference that provides rapid dissemination of novel research results in the BCI community. Participants can submit abstracts to apply for 20 minutes presentation slots. Abstracts are not reviewed by a program committee. Rather, all registered participants can vote on which of the submitted abstracts they would like to see presented at the un-conference. Because the BCI-UC does not publish conference proceedings, submitted abstracts can report novel as well as already published work. Registration and attendance are free of charge. Presentations of the 1st and 2nd BCI-UC can be re-watched [4]. Join us in setting the BCIUC agenda! The BCI-UC committee: Moritz Grosse-Wentrup Anja Meunier Philipp Raggam Jiachen Xu Links: [1] https://bciunconference.univie.ac.at/register-vote/ [2] https://scholar.google.com/citations?user=36sxAZEAAAAJ&hl=de [3] https://scholar.google.com/citations?hl=en&user=0E49HxYAAAAJ [4] https://bciunconference.univie.ac.at/past-events/ Links: ------ [1] https://bciunconference.univie.ac.at/register-vote/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From pubconference at gmail.com Mon Dec 6 21:16:18 2021 From: pubconference at gmail.com (Pub Conference) Date: Mon, 6 Dec 2021 21:16:18 -0500 Subject: Connectionists: [Journal] Call for IEEE TNNLS Special Issue on "Stream Learning, " Submission Deadline: December 15, 2021 Message-ID: IEEE TNNLS Special Issue on "Stream Learning," Guest Editors: Jie Lu, University of Technology Sydney, Australia; Joao Gama, University of Porto, Portugal; Xin Yao, Southern University of Science and Technology, China; Leandro Minku, University of Birmingham, UK. Submission Deadline: December 15, 2021 [EXTENDED]. Website: https://cis.ieee.org/images/files/Publications/TNNLS /special-issues/One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf Type: application/pdf Size: 109969 bytes Desc: not available URL: From graduateprograms at bccn-berlin.de Tue Dec 7 03:37:55 2021 From: graduateprograms at bccn-berlin.de (Graduate Programs) Date: Tue, 7 Dec 2021 09:37:55 +0100 Subject: Connectionists: Digital Info Day - International Master & PhD in Computational Neuroscience @ BCCN Berlin - 26.01.22 Message-ID: <8442f952-79e5-b042-2bfa-a21f8cd85702@bccn-berlin.de> Dear Connectionists, Please share the following event information with anyone who may be interested. We at the Bernstein Center for Computational Neuroscience (BCCN) Berlin will hold a hybrid "Info Day" to discuss our International Master & Doctoral Programs in Computational Neuroscience on Wednesday, January 26th, at 3pm (CET). The event will consist of talks by: * Prof. Dr. Klaus Obermayer (head of the programs) * Lisa Velenosi (teaching coordinator) * Current master and doctoral students Attendees will also have the opportunity to meet & discuss with current students and ask any questions or concerns that they may have. See our website for a more detailed schedule and registration link. Best regards and I hope that everyone is staying healthy, Lisa Velenosi -- Lisa Velenosi Teaching Coordinator Bernstein Center for Computational Neuroscience Humboldt-Universit?t zu Berlin Philippstra?e 13, Haus 6; 10115 Berlin; Germany Tel: +49 (0)30 2093 6773 Technische Universit?t Berlin Marchstra?e 23; Raum 5.061; 10587 Berlin; Germany Tel: +49 (0)30 314 72006 SFB1315 - Network Outreach Coordinator PhD & Postdoc Cohort -------------- next part -------------- An HTML attachment was scrubbed... URL: From H.Bowman at kent.ac.uk Sat Dec 4 07:13:34 2021 From: H.Bowman at kent.ac.uk (Howard Bowman) Date: Sat, 4 Dec 2021 12:13:34 +0000 Subject: Connectionists: PhD position with neural modelling component Message-ID: Identifying the Role of Conscious Perception: a Neuroimaging and Computational Investigation ------------------------------------------------------------------------------------------------------------------------------- Dr H Bowman, Dr D Cruse (School of Psychology, University of Birmingham) (Deadline: Sunday, January 09, 2022) About the Project The question of what conscious perception is for remains a key, largely unanswered, question for the scientific study of consciousness and indeed for our whole understanding of mind. In fact, a substantial part of the scientific study of consciousness has focused on showing how sophisticated subconscious processing can be, seemingly leaving little room for a "special" purpose for conscious experience. We have recently presented empirical evidence, which suggests that the subconscious brain is limited in its capacity to represent episodic information (Avil?s, Bowman & Wyble, 2020; Bowman, Filetti, Alsufyani, Janssen & Su, 2014). By episodic, we are particularly emphasizing the capacity to associate percepts with the passage of time, something that we humans do so easily consciously that we hardly notice it. This work uses Rapid Serial Visual Presentation (RSVP) to present stimuli on the fringe of awareness. In Avil?s, Bowman & Wyble (2020), we showed that the capacity to consciously perceive a stimulus does not benefit from repeating it unless it has been consciously perceived previously. Repetition is a key episodic property, i.e. to know that a presentation of a stimulus is a repetition, the brain has to have a memory of a previous episode of experiencing the stimulus. Additionally, if the RSVP stream of stimuli is slowed down sufficiently that the viewer consciously observes every stimulus, it becomes trivially easy to perform the task of detecting the repeating item. The strong claim, then, is that a specific capacity provided by conscious perception is to lay down freely-recallable episodic memories of previous experiences. We now have extensive behavioural evidence for this hypothesis, a good deal of which will shortly appear in print. We are thus at a perfect stage to 1) characterise the neural correlates that support this formation of freely-recallable episodic memories, and 2) explain these findings with the computational theory that underlies our work in this area: the Simultaneous Type/ Serial Token model (Bowman & Wyble, 2007). Accordingly, we are proposing a PhD to work on one or both of these topics. The first of these research activities, characterising neural correlates, could employ fMRI, MEG or EEG (all of which are available to us), with the latter two being particularly relevant because of their high temporal resolution. This line of research could take our existing RSVP behavioural paradigms and seek to identify neural components that are engaged when a stimulus presentation leads to the later detection of a repetition. This would give a new way to identify the neural components that are specific to conscious processing, with relevance to debates concerning whether the neural correlates of conscious processing reside in the sensory processing pathways or at a later, brain-scale, stage. Oscillatory correlates of conscious processing and episodic memory formation are of particular interest (Parish, Hanslmayr & Bowman, 2018). The second research activity, computational modelling, would involve simulating the repetition effects and resulting correlates of conscious processing, with the Simultaneous Type/ Serial Token - a well attested theory of temporal attention and episodic encoding into working-memory (Bowman & Wyble, 2007). This neural network model is consistent with brain-scale state theories of conscious perception, such as the global workspace. For further details, contact Professor Howard Bowman (H.Bowman at bham.ac.uk) Funding Notes This PhD is funded by the Midlands Integrative Biosciences Training Partnership (MIBTP). Funding covers fees and stipend. For more details, look at these pages: https://warwick.ac.uk/fac/cross_fac/mibtp/ https://www.birmingham.ac.uk/research/activity/mibtp/index.aspx Both home and International students can apply (EU students are now classed as international). References Avil?s, Bowman & Wyble (2020). On the limits of evidence accumulation of the preconscious percept. Cognition, 195. Bowman & Wyble (2007). The simultaneous type, serial token model of temporal attention and working memory. Psychological review, 114(1), 38. Bowman et al. (2014). Countering countermeasures: detecting identity lies by detecting conscious breakthrough. PloS one, 9(3). Parish, Hanslmayr & Bowman (2018). The sync/desync model: How a synchronized hippocampus and a desynchronized neocortex code memories. Journal of Neuroscience, 38(14), 3428-3440. -------------------------------------------- Professor Howard Bowman (PhD) Professor of Cognition & Logic in Computing at Uni Kent, and Professor of Cognitive Neuroscience in Psychology at Uni Birmingham (visiting at Wellcome Centre for Human Neuroimaging, University College London) Centre for Cognitive Neuroscience and Cognitive Systems and the School of Computing, University of Kent at Canterbury, Canterbury, Kent, CT2 7NF, UK email: H.Bowman at kent.ac.uk WWW: http://www.cs.kent.ac.uk/people/staff/hb5/ School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK -------------- next part -------------- An HTML attachment was scrubbed... URL: From rpaudel142 at gmail.com Mon Dec 6 12:26:55 2021 From: rpaudel142 at gmail.com (Ramesh Paudel) Date: Mon, 6 Dec 2021 12:26:55 -0500 Subject: Connectionists: CFP - Deep Learning for IoT Security - Frontiers in Big Data Message-ID: Dear All, We are pleased to be launching a new Research Topic, Deep Learning for IoT Security. We?re putting together a group of top researchers whose work we?d like to feature in this collection, and I thought you would be interested in participating. Hosted by Frontiers in Big Data, this is a unique opportunity for us to collaborate and to showcase your research. This Research Topic focuses on recent advances in research and development in securing the IoT landscape using deep learning. The objective of this collection is to bring together researchers from both deep learning and cybersecurity domains to provide a venue to share ideas and foster knowledge on IoT security challenges and solutions. Papers can be from any of the following areas, including but not limited to: ? Vehicular ad-hoc network, smart home, healthcare, and smart meter security ? Real-time/anti-adversarial/efficient deep learning security protocols/solutions ? Intrusion detection and prevention ? Malware detection ? Data security and privacy ? Anomaly detection in authentication, authorization, and data requests ? Adversarial machine learning and the robustness ofAI models against malicious actions ? Interpretability and explainability of deep learning models ? Privacy-preserving deep learning algorithms ? Trustworthy deep learning ? Deep graph learning ? Fog-based IoT security ? Sensor network security ? Cloud-based IoT security Please let us know if you wish to participate: https://research-topic-management-app.frontiersin.org/manage/contributor-confirms-participation?activationkey=b87fde81-68d2-4b9f-9eb4-a6adacd1af1d *Submission deadline*: *31 January 2022* All submitted articles are peer reviewed. Article processing charges are applied to all published articles. ? See if your institution has a payment plan with us. (see here: https://www.frontiersin.org/about/institutional-membership ) ? Find out about applying for fee support (see here https://www.frontiersin.org/about/publishing-fees#feesupport ) Please let us know if you don?t wish to participate this time: https://research-topic-management-app.frontiersin.org/manage/contributor-declines-participation?activationkey=b87fde81-68d2-4b9f-9eb4-a6adacd1af1d *About Frontiers in Big Data* Leading research exploring how big data can help address global challenges. The journal is led by Field Chief Editor Huan Liu from Arizona State University. Frontiers is the world's third most-cited publisher with more than 2.2 million citations and 1.4 billion views and downloads from global research and innovation hubs. *About Research Topics* Frontiers? Research Topics multidisciplinary article collections bringing together leading experts in the field. Designed for impact, these collections are highly cited and widely read by researchers across the world. Find out more about Research Topics (see https://www.frontiersin.org/about/research-topics). Kind Regards, Ramesh Paudel, Ph.D. Topic Editor, Cybersecurity and Privacy Section, Frontiers in Big Data -------------- next part -------------- An HTML attachment was scrubbed... URL: From cgf at isep.ipp.pt Mon Dec 6 14:25:41 2021 From: cgf at isep.ipp.pt (Carlos) Date: Mon, 6 Dec 2021 19:25:41 +0000 Subject: Connectionists: NetSciX 2022 - Final Call for Submissions: December 8 Message-ID: ** (Last Call for Submissions) ** ** We have extended the submission deadline for a ** ** few more days until the 8th of December, 2021 ** ================================== International School and Conference on Network Science NetSci-X 2022 Porto, Portugal February 8-11, 2022 https://netscix.dcc.fc.up.pt/ ================================== Important Dates ----------------------------- Full Paper/Abstract Submission: December 8, 2021 (23:59:59 AoE) Author Notification: December 28, 2021 Keynote Speakers ----------------------------- Jure Leskovec, Stanford University, USA Jurgen Kurths, Humboldt University Berlin, Germany Manuela Veloso, JP Morgan AI Research & CMU, USA Stefano Boccaletti, Institute for Complex Systems, Florence, Italy Tijana Milenkovic, University of Notre Dame, USA Tiziana Di Matteo, King's College London, UK Invited Speakers ----------------------------- Ang?lica Sousa de Mata, Universidade Federal de Lavras, Brazil Francisco Santos, University of Lisbon, Portugal Marcus Kaiser, University of Nottingham, UK Maria Angeles Serrano, University of Barcelona, Spain Marta C. Gonz?lez, University of California, Berkeley, USA Sune Lehmann, TU Denmark / University of Copenhagen, Denmark Tracks ----------------------------- We are welcoming submissions to the Abstracts or Proceedings Track. All submissions will undergo a peer-review process. Abstracts Track: extended abstracts should not exceed 3 pages, including figures and references. Abstracts will be accepted for oral or poster presentation, and will appear in the book of abstracts only. Proceedings Track: full papers should have between 8 and 14 pages and follow the Springer Proceedings format. Accepted full papers will be presented at the conference and published by Springer. Only previously unpublished, original submissions will be accepted. Description ----------------------------- NetSci-X is the Network Science Society?s signature winter conference. It extends the popular NetSci conference series (https://netscisociety.net/events/netsci) to provide an additional forum for a growing community of academics and practitioners working on formal, computational, and application aspects of complex networks. The conference will be highly interdisciplinary, spanning the boundaries of traditional disciplines. Specific topics of interest include (but are not limited to): Models of Complex Networks Structural Network Properties Algorithms for Network Analysis Graph Mining Large-Scale Graph Analytics Epidemics Resilience and Robustness Community Structure Motifs and Subgraph Patterns Link Prediction Multilayer/Multiplex Networks Temporal and Spatial Networks Dynamics on and of Complex Networks Network Controllability Synchronization in Networks Percolation, Resilience, Phase Transitions Network Geometry Network Neuroscience Network Medicine Bioinformatics and Earth Sciences Applications Mobility and Urban Networks Computational Social Sciences Rumor and Viral Marketing Economics and Financial Networks Instructions for Submissions ----------------------- All papers and abstracts should be submitted electronically in PDF format. The website includes detailed information about the submission process. General Chairs Fernando Silva, University of Porto, Portugal Jos? Mendes, University of Aveiro, Portugal Ros?rio Laureano, Lisbon University Institute (ISCTE), Portugal Program Chair Pedro Ribeiro, Universidade do Porto, Portugal School Chairs Manuel Pita, CICANT, Universidade Lusofona, Portugal Andreia Sofia Teixeira, University of Lisbon, Portugal Main Contact for NetSci-X 2022 netscix at dcc.fc.up.pt Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. Ant?nio Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From maanakg at gmail.com Fri Dec 3 12:13:54 2021 From: maanakg at gmail.com (Maanak Gupta) Date: Fri, 3 Dec 2021 11:13:54 -0600 Subject: Connectionists: Call for Papers: 27th ACM Symposium on Access Control Models and Technologies Message-ID: ACM SACMAT 2022 New York City, New York ----------------------------------------------- | Hybrid Conference (Online + In-person) | ----------------------------------------------- Call for Research Papers ============================================================== Papers offering novel research contributions are solicited for submission. Accepted papers will be presented at the symposium and published by the ACM in the symposium proceedings. In addition to the regular research track, this year SACMAT will again host the special track -- "Blue Sky/Vision Track". Researchers are invited to submit papers describing promising new ideas and challenges of interest to the community as well as access control needs emerging from other fields. We are particularly looking for potentially disruptive and new ideas which can shape the research agenda for the next 10 years. We also encourage submissions to the "Work-in-progress Track" to present ideas that may have not been completely developed and experimentally evaluated. Topics of Interest ============================================================== Submissions to the regular track covering any relevant area of access control are welcomed. Areas include, but are not limited to, the following: * Systems: * Operating systems * Cloud systems and their security * Distributed systems * Fog and Edge-computing systems * Cyber-physical and Embedded systems * Mobile systems * Autonomous systems (e.g., UAV security, autonomous vehicles, etc) * IoT systems (e.g., home-automation systems) * WWW * Design for resiliency * Designing systems with zero-trust architecture * Network: * Network systems (e.g., Software-defined network, Network function virtualization) * Corporate and Military-grade Networks * Wireless and Cellular Networks * Opportunistic Network (e.g., delay-tolerant network, P2P) * Overlay Network * Satellite Network * Privacy and Privacy-enhancing Technologies: * Mixers and Mixnets * Anonymous protocols (e.g., Tor) * Online social networks (OSN) * Anonymous communication and censorship resistance * Access control and identity management with privacy * Cryptographic tools for privacy * Data protection technologies * Attacks on Privacy and their defenses * Authentication: * Password-based Authentication * Biometric-based Authentication * Location-based Authentication * Identity management * Usable authentication * Mechanisms: * Blockchain Technologies * AI/ML Technologies * Cryptographic Technologies * Programming-language based Technologies * Hardware-security Technologies (e.g., Intel SGX, ARM TrustZone) * Economic models and game theory * Trust Management * Usable mechanisms * Data Security: * Big data * Databases and data management * Data leakage prevention * Data protection on untrusted infrastructure * Policies and Models: * Novel policy language design * New Access Control Models * Extension of policy languages * Extension of Models * Analysis of policy languages * Analysis of Models * Policy engineering and policy mining * Verification of policy languages * Efficient enforcement of policies * Usable access control policy New in ACM SACMAT 2022 ============================================================== We are moving ACM SACMAT 2022 to have two submission cycles. Authors submitting papers in the first submission cycle will have the opportunity to receive a major revision verdict in addition to the usual accept and reject verdicts. Authors can decide to prepare a revised version of the paper and submit it to the second submission cycle for consideration. Major revision papers will be reviewed by the program committee members based on the criteria set forward by them in the first submission cycle. Regular Track Paper Submission and Format ============================================================== Papers must be written in?English. Authors are required to use the ACM format for papers, using the two-column SIG Proceedings Template (the sigconf template for LaTex) available in the following link: https://www.acm.org/publications/authors/submissions The length of the paper in the proceedings format must not exceed?twelve?US letter pages formatted for 8.5" x 11" paper and be no more than 5MB in size. It is the responsibility of the authors to ensure that their submissions will print easily on simple default configurations. The submission must be anonymous, so information that might identify the authors - including author names, affiliations, acknowledgments, or obvious self-citations - must be excluded. It is the authors' responsibility to ensure that their anonymity is preserved when citing their work. Submissions should be made to the EasyChair conference management system by the paper submission deadline of: November 15th, 2021 (Submission Cycle 1) February 18th, 2022 (Submission Cycle 2) Submission Link: https://easychair.org/conferences/?conf=acmsacmat2022 All submissions must contain a significant original contribution. That is, submitted papers must not substantially overlap papers that have been published or that are simultaneously submitted to a journal, conference, or workshop. In particular, simultaneous submission of the same work is not allowed. Wherever appropriate, relevant related work, including that of the authors, must be cited. Submissions that are not accepted as full papers may be invited to appear as short papers. At least one author from each accepted paper must register for the conference before the camera-ready deadline. Blue Sky Track Paper Submission and Format ============================================================== All submissions to this track should be in the same format as for the regular track, but the length must not exceed ten US letter pages, and the submissions are not required to be anonymized (optional). Submissions to this track should be submitted to the EasyChair conference management system by the same deadline as for the regular track. Work-in-progress Track Paper Submission and Format ============================================================== Authors are invited to submit papers in the newly introduced work-in-progress track. This track is introduced for (junior) authors, ideally, Ph.D. and Master's students, to obtain early, constructive feedback on their work. Submissions in this track should follow the same format as for the regular track papers while limiting the total number of pages to six US letter pages. Paper submitted in this track should be anonymized and can be submitted to the EasyChair conference management system by the same deadline as for the regular track. Call for Lightning Talk ============================================================== Participants are invited to submit proposals for 5-minute lightning talks describing recently published results, work in progress, wild ideas, etc. Lightning talks are a new feature of SACMAT, introduced this year to partially replace the informal sharing of ideas at in-person meetings. Submissions are expected??by May 27, 2022. Notification of acceptance will be on June 3, 2022. Call for Posters ============================================================== SACMAT 2022 will include a poster session to promote discussion of ongoing projects among researchers in the field of access control and computer security. Posters can cover preliminary or exploratory work with interesting ideas, or research projects in the early stages with promising results in all aspects of access control and computer security. Authors interested in displaying a poster must submit a poster abstract in the same format as for the regular track, but the length must not exceed three US letter pages, and the submission should not be anonymized. The title should start with "Poster:". Accepted poster abstracts will be included in the conference proceedings. Submissions should be emailed to the poster chair by Apr 15th, 2022. The subject line should include "SACMAT 2022 Poster:" followed by the poster title. Call for Demos ============================================================== A demonstration proposal should clearly describe (1) the overall architecture of the system or technology to be demonstrated, and (2) one or more demonstration scenarios that describe how the audience, interacting with the demonstration system or the demonstrator, will gain an understanding of the underlying technology. Submissions will be evaluated based on the motivation of the work behind the use of the system or technology to be demonstrated and its novelty. The subject line should include "SACMAT 2022 Demo:" followed by the demo title. Demonstration proposals should be in the same format as for the regular track, but the length must not exceed four US letter pages, and the submission should not be anonymized. A two-page description of the demonstration will be included in the conference proceedings. Submissions should be emailed to the Demonstrations Chair by Apr 15th, 2022. Financial Conflict of Interest (COI) Disclosure: ============================================================== In the interests of transparency and to help readers form their own judgments of potential bias, ACM SACMAT requires authors and PC members to declare any competing financial and/or non-financial interests in relation to the work described. Definition ------------------------- For the purposes of this policy, competing interests are defined as financial and non-financial interests that could directly undermine, or be perceived to undermine the objectivity, integrity, and value of a publication, through a potential influence on the judgments and actions of authors with regard to objective data presentation, analysis, and interpretation. Financial competing interests include any of the following: Funding: Research support (including salaries, equipment, supplies, and other expenses) by organizations that may gain or lose financially through this publication. A specific role for the funding provider in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript, should be disclosed. Employment: Recent (while engaged in the research project), present or anticipated employment by any organization that may gain or lose financially through this publication. Personal financial interests: Ownership or contractual interest in stocks or shares of companies that may gain or lose financially through publication; consultation fees or other forms of remuneration (including reimbursements for attending symposia) from organizations that may gain or lose financially; patents or patent applications (awarded or pending) filed by the authors or their institutions whose value may be affected by publication. For patents and patent applications, disclosure of the following information is requested: patent applicant (whether author or institution), name of the inventor(s), application number, the status of the application, specific aspect of manuscript covered in the patent application. It is difficult to specify a threshold at which a financial interest becomes significant, but note that many US universities require faculty members to disclose interests exceeding $10,000 or 5% equity in a company. Any such figure is necessarily arbitrary, so we offer as one possible practical alternative guideline: "Any undeclared competing financial interests that could embarrass you were they to become publicly known after your work was published." We do not consider diversified mutual funds or investment trusts to constitute a competing financial interest. Also, for employees in non-executive or leadership positions, we do not consider financial interest related to stocks or shares in their company to constitute a competing financial interest, as long as they are publishing under their company affiliation. Non-financial competing interests: Non-financial competing interests can take different forms, including personal or professional relations with organizations and individuals. We would encourage authors and PC members to declare any unpaid roles or relationships that might have a bearing on the publication process. Examples of non-financial competing interests include (but are not limited to): * Unpaid membership in a government or non-governmental organization * Unpaid membership in an advocacy or lobbying organization * Unpaid advisory position in a commercial organization * Writing or consulting for an educational company * Acting as an expert witness Conference Code of Conduct and Etiquette ============================================================== ACM SACMAT will follow the ACM Policy Against Harassment at ACM Activities. Please familiarize yourself with the ACM Policy Against Harassment (available at https://www.acm.org/special-interest-groups/volunteer-resources/officers-manual/ policy-against-discrimination-and-harassment) and guide to Reporting Unacceptable Behavior (available at https://www.acm.org/about-acm/reporting-unacceptable-behavior). AUTHORS TAKE NOTE ============================================================== The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks before the first day of your conference. The official publication date affects the deadline for any patent filings related to published work. (For those rare conferences whose proceedings are published in the ACM Digital Library after the conference is over, the official publication date remains the first day of the conference.) Important dates ============================================================== **Note that, these dates are currently only tentative and subject to change.** * Paper submission: November 15th, 2021 (Submission Cycle 1) February 18th, 2022 (Submission Cycle 2) * Rebuttal: December 16th - December 20th, 2021 (Submission Cycle 1) March 24th - March 28th, 2022 (Submission Cycle 2) * Notifications: January 14th, 2022 (Submission Cycle 1) April 8th, 2022 (Submission Cycle 2) * Systems demo and Poster submissions: April 15th, 2022 * Systems demo and Poster notifications: April 22nd, 2022 * Panel Proposal: March 18th, 2022 * Camera-ready paper submission: April 29th, 2022 * Conference date: June 8 - June 10, 2022 -------------- next part -------------- An HTML attachment was scrubbed... URL: From george at cs.ucy.ac.cy Sat Dec 4 07:03:48 2021 From: george at cs.ucy.ac.cy (George A. Papadopoulos) Date: Sat, 4 Dec 2021 14:03:48 +0200 Subject: Connectionists: ACM International Conference on Information Technology for Social Good (GoodIT 2022): Last Call for Special Track Proposals Message-ID: *** Last Call for Special Track Proposals *** ACM International Conference on Information Technology for Social Good (GoodIT 2022) 7?9 September, 2022, 5* St. Raphael Resort & Marina, Limassol, Cyprus https://cyprusconferences.org/goodit2022/ Scope ACM GoodIT focuses on the application of IT technologies to social good. Social good is typically defined as an action that provides some sort of benefit to the general public. In this case, Internet connection, education, and healthcare are all good examples of social goods. However, new media innovations and the explosion of online communities have added new meaning to the term. Social good is now about global citizens uniting to unlock the potential of individuals, technology, and collaboration to create positive societal impact. GoodIT topics include but not limited to: ? IT for education ? Data Science ? Digital solutions for Cultural Heritage ? Data sensing, processing, and persistency ? Game, entertainment, and multimedia applications ? Health and social care ? IT for development ? Privacy and trust issues and solutions ? Sustainable cities and transportation ? Smart governance and e-administration ? IT for smart living ? Technology addressing the digital divide ? IT for automotive ? Frugal solutions for IT ? Ethical computing ? Decentralized approaches to IT ? Citizen science ? Socially responsible IT solutions ? Sustainable IT ? Social informatics ? Civic intelligence Journal Special Issue and Best Paper Award Selected papers will be invited to submit an extended version to a special issue in the journal MDPI Sensors, where the theme of the special issue will be "Application of Information Technology (IT) to Social Good" (https://www.mdpi.com/journal/sensors/special_issues/topical_collection_goodit). Specifically 5 papers will be invited free of charge and another 5 papers will get a 20% discount on the publication fees. Furthermore, MDPI Sensors will sponsor a Best Paper Award with the amount of 400 CHF. Special Tracks Proposals GoodIT 2022 will feature special tracks whose aim is to focus on a specific topic of interest related to the overall scope of the conference. We solicit proposals for special tracks to be held within the main conference and whose publications will be included in the conference proceedings. Tracks proposals can focus on any contemporary themes that highlight social good aspects in the design, implementation, deployment, securing, and evaluation of IT technologies. Special Track Proposal Format A special track proposal must contain the following information: ? Title of the special track. ? The names of the organizers (indicatively, two) with affiliations, contact information, and a single paragraph of a brief bio. ? A short description of the scope and topics of the track (max 1/2 page) and a brief explanation of: (1) why the topic is timely and important; (2) why the topic is related to the conference?s main theme; (3) why the track may attract a significant number of submissions of good quality. ? Indication if a journal special issue is associated with the track, possibly with information on the process of selecting papers. ? The plan to disseminate the call for papers of the special track for achieving a reasonable number of paper submissions (a list of emailing lists will help). ? A tentative Program Committee list. ? A draft Call for Papers (max 1 page). Publication Papers submitted to each particular track have to satisfy the same criteria as for the main conference. They must be original works and must not have been previously published. They have to be peer-reviewed by the track's Program Committee (at least three reviews per submitted paper are required). The final version of papers must follow the formatting instructions of the main conference (https://cyprusconferences.org/goodit2022/index.php/authors/). At least one of the authors of all accepted papers must register and present the work at the conference; otherwise, the paper will not be published in the proceedings. All accepted and presented papers will be included in the conference proceedings published in the ACM Digital Library. The special track may provide an option for publishing extended versions of selected papers in a special issue of a journal. Special Track Proposal Submission Guidelines Special track proposals should be submitted as a single PDF file to the special track Chairs (see below) via email to: ombretta.gaggi at unipd.it, valentino.vranic at stuba.sk, and rysavy at fit.vut.cz. The subject of the e-mail must be: ?GoodIT 2022 ? special track proposal?. The special track chairs may ask proposers for supplying additional information during the review period. Important Dates ? Special Track Proposal Submission Deadline: 13 December 2021 ? Notification of Selection: 20 December 2021 Contact (Special Tracks Chairs) ? Ombretta Gaggi (University of Padua, Italy) ? Ondrej Rysavy (Brno University of Technology, Czech Republic) ? Valentino Vranic (Slovak University of Technology in Bratislava, Slovakia) -------------- next part -------------- An HTML attachment was scrubbed... URL: From alessandra.sciutti at gmail.com Mon Dec 6 09:57:35 2021 From: alessandra.sciutti at gmail.com (alessandra.sciutti at gmail.com) Date: Mon, 6 Dec 2021 15:57:35 +0100 Subject: Connectionists: [CfP] Special Issue in IEEE Transactions on Cognitive and Developmental Systems (TCDS) - Second Edition Message-ID: <012101d7eab1$9aa478a0$cfed69e0$@gmail.com> ======================================================================= Call for Papers - Special Issue in IEEE Transactions on Cognitive and Developmental Systems ======================================================================== Dear Colleagues, Following up on the success of the ICDL 2021 conference, we are pleased to announce a second edition on the special issue in the IEEE Transactions on Cognitive and Developmental Systems (TCDS) on related topics. Below are the relevant details. Quick Links ================= *Second Edition of the Special Issue on Emerging Topics on Development and Learning* Journal: IEEE Transactions on Cognitive and Developmental Systems (TCDS) Journal Link: https://cis.ieee.org/publications/t-cognitive-and-developmental-systems Special Issue: https://wanweiwei07.github.io/files/ICDL2021_Special_Issue_Proposal_IEEE_For mat.pdf Tentative timeline ================ *Submission deadline (extended): 15 January 2022* First Reviews Completed: 15 March 2022 Final Decision: 30 June 2022 Overview ======== This special issue aims to track the state-of-the-art progress on development and learning in natural and artificial systems. It concentrates on development and learning from a multidisciplinary perspective. Researchers from computer science, robotics, psychology, and developmental studies are solicited to share their knowledge and research on how humans and animals develop sensing, reasoning and actions, and how to exploit robots as research tools to test models of development and learning. We expect the submitted contributions emphasize the interaction with social and physical environments and how cognitive and developmental capabilities can be transferred to computing systems and robotics. This approach goes hand in hand with the goals of both understanding human and animal development and applying this knowledge to improve future intelligent technology, including for robots that will be in close interaction with humans. The primary list of topics of interest include, but not limited to: - Principles and theories of development and learning; - Development of skills in biological systems and robots; - Models on the contributions of interaction to learning; - Non-verbal and multi-modal interaction; - Nature vs. nurture, developmental stages; - Models on active learning; - Architectures for lifelong learning; - Emergence of body and affordance perception; - Analysis and modelling of human motion and state; - Models for prediction, planning and problem solving; - Models of human-human and human-robot interaction; - Emergence of verbal and non-verbal communication; - Epistemological foundations and philosophical issues; - Robot prototyping of human and animal skills; - Ethics and trust in computational intelligence and robotics; - Social learning in humans, animals, and robots. Contributions ============ The special issue is open to novel contributions. Also extended versions of published conference papers (such as in ICDL 2021) are welcome, but they must have at least 30% new impacting technical/scientific material in the submitted journal version, and there should be less than 50% verbatim similarity as reported by a tool (such as CrossRef). Additionally, the conference papers and the detailed summary differences must be included as part of the journal submission to TCDS. All submissions will be reviewed as regular TCDS papers before acceptance. Guest Editors =========== - Dingsheng Luo (Lead guest editor) (dsluo at pku.edu.cn) - Angelo Cangelosi (angelo.cangelosi at manchester.ac.uk) - Alessandra Sciutti (alessandra.sciutti at iit.it) - Weiwei Wan (wan at sys.es.osaka-u.ac.jp) - Ana Tanevska (ana.tanevska at iit.it) For further information, please contact the editors. Regards, Alessandra (on behalf of all the Guest Editors) ---------------------------------------- Alessandra Sciutti (PhD) Researcher Tenure Track - P.I. CONTACT Unit Istituto Italiano di Tecnologia - Via Enrico Melen 83, Building B 16152 Genova, Italy email: alessandra.sciutti at iit.it website: https://www.iit.it/people/alessandra-sciutti ERC website: https://www.whisperproject.eu/ An intro on my research (Video, Eng): https://youtu.be/LCkOjR_cvxI TEDx talk (Italian): https://www.youtube.com/watch?reload=9&v=e0eMayWU_lc Our book on Modeling Human Motion: https://www.springer.com/gp/book/9783030467319 twitter: @alefreedot -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sat Dec 4 12:16:29 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sat, 4 Dec 2021 18:16:29 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Spring - DeepLearn 2022 Summer Message-ID: <534594527.976570.1638638189868@webmail.strato.com> Dear all, DeepLearn, the International School on Deep Learning, is running since 2017 successfully. Please note the next editions of the program in 2022: https://irdta.eu/deeplearn/2022sp/ https://irdta.eu/deeplearn/2022su/ Best regards, DeepLearn organizing team -------------- next part -------------- An HTML attachment was scrubbed... URL: From jsmagnuson at gmail.com Sat Dec 4 18:36:18 2021 From: jsmagnuson at gmail.com (Jim Magnuson) Date: Sat, 4 Dec 2021 18:36:18 -0500 Subject: Connectionists: funded PhD in computational modeling of bilingualism at BCBL Message-ID: - 3-year Ph.D. position (master's degree required) - Funded by la Caixa Foundation - Focus: The computational and neural bases of bilingualism: A complementary learning systems model (projects must be related to this theme, but are flexible) - Location: Basque Center on Cognition, Brain, and Language; San Sebastian, Spain - Group: Computational Neuroscience - Leader: Jim Magnuson - Deadline: January 27 - Applicants are encouraged to contact Jim Magnuson before applying - Application portal: https://finder.lacaixafellowships.org/finder?position=4739 -------------- next part -------------- An HTML attachment was scrubbed... URL: From george at cs.ucy.ac.cy Sun Dec 5 07:44:49 2021 From: george at cs.ucy.ac.cy (George A. Papadopoulos) Date: Sun, 5 Dec 2021 14:44:49 +0200 Subject: Connectionists: 2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS 2022): Fifth Call for Papers Message-ID: *** Fifth Call for Papers *** 2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS 2022) May 25-27, 2022, Golden Bay Hotel 5*, Larnaca, Cyprus http://cyprusconferences.org/eais2022/ (Proceedings to be published by the IEEE Xplore Digital Library; Special Journal Issue with Evolving Systems, Springer) IEEE EAIS 2022 will provide a working and friendly atmosphere and will be a leading international forum focusing on the discussion of recent advances, the exchange of recent innovations and the outline of open important future challenges in the area of Evolving and Adaptive Intelligent Systems. Over the past decade, this area has emerged to play an important role on a broad international level in today's real-world applications, especially those ones with high complexity and dynamic changes. Its embedded modelling and learning methodologies are able to cope with real-time demands, changing operation conditions, varying environmental influences, human behaviours, knowledge expansion scenarios and drifts in online data streams. Conference Topics Basic Methodologies Evolving Soft Computing Techniques. Evolving Fuzzy Systems. Evolving Rule-Based Classifiers. Evolving Neuro-Fuzzy Systems. Adaptive Evolving Neural Networks. Online Genetic and Evolutionary Algorithms. Data Stream Mining. Incremental and Evolving Clustering. Adaptive Pattern Recognition. Incremental and Evolving ML Classifiers. Adaptive Statistical Techniques. Evolving Decision Systems. Big Data. Problems and Methodologies in Data Streams Stability, Robustness, Convergence in Evolving Systems. Online Feature Selection and Dimension Reduction. Online Active and Semi-supervised Learning. Online Complexity Reduction. Computational Aspects. Interpretability Issues. Incremental Adaptive Ensemble Methods. Online Bagging and Boosting. Self-monitoring Evolving Systems. Human-Machine Interaction Issues. Hybrid Modelling, Transfer Learning. Reservoir Computing. Applications of EAIS Time Series Prediction. Data Stream Mining and Adaptive Knowledge Discovery. Robotics. Intelligent Transport and Advanced Manufacturing. Advanced Communications and Multimedia Applications. Bioinformatics and Medicine. Online Quality Control and Fault Diagnosis. Condition Monitoring Systems. Adaptive Evolving Controller Design. User Activities Recognition. Huge Database and Web Mining. Visual Inspection and Image Classification. Image Processing. Cloud Computing. Multiple Sensor Networks. Query Systems and Social Networks. Alternative Statistical and Machine Learning Approaches. Submissions Submitted papers should not exceed 8 pages plus at most 2 pages overlength. Submissions of full papers are accepted online through Easy Chair (https://easychair.org/conferences/?conf=eais2022). The EAIS 2022 proceedings will be published on IEEE Xplore Digital Library. Authors of selected papers will be invited to submit extended versions for possible inclusion in a special issue of Evolving Systems - An Interdisciplinary Journal for Advanced Science and Technology (Springer). Important Dates ? Paper submission: January 10, 2022 ? Notification of acceptance/rejection: February 19, 2022 ? Camera ready submission: March 20, 2022 ? Authors registration: March 20, 2022 ? Conference Dates: May 25-27, 2022 Social Media FB: https://www.facebook.com/IEEEEAIS Twitter: https://twitter.com/IEEE_EAIS Linkedin: https://www.linkedin.com/events/2022ieeeconferenceonevolvingand6815560078674972672/ Organization Honorary Chairs ? Dimitar Filev, Ford Motor Co., USA ? Nikola Kasabov, Auckland University of Technology, New Zealand General Chairs ? George A. Papadopoulos, University of Cyprus, Nicosia, Cyprus ? Plamen Angelov, Lancaster University, UK Program Committee Chairs ? Giovanna Castellano, University of Bari, Italy ? Jos? A. Iglesias, Carlos III University of Madrid, Spain -------------- next part -------------- An HTML attachment was scrubbed... URL: From jpezaris at gmail.com Fri Dec 3 17:44:24 2021 From: jpezaris at gmail.com (John Pezaris) Date: Fri, 3 Dec 2021 17:44:24 -0500 Subject: Connectionists: AREADNE 2022 Call for Abstracts Message-ID: AREADNE 2022 Research in Encoding and Decoding of Neural Ensembles Nomikos Conference Centre, Santorini, Greece 28 June - 2 July 2022 http://areadne.org info at areadne.org Dear Colleague, We are pleased to announce solicitation of abstracts for poster presentation at AREADNE 2022, 28 June - 2 July 2022, our ninth meeting to be held at the Nomikos Conference Centre in Santorini, Greece. Continuing with the same highly successful format, AREADNE 2022 will bring scientific leaders from around the world to present their theoretical and experimental work on the functioning of neuronal ensembles. The meeting will provide an informal yet spectacular setting in which attendees can discuss their recent ideas and discoveries, with a relaxed pace that emphasizes interaction. Please see the Call for Abstracts for additional details, including links for templates, at http://areadne.org/call-for-abstracts Submissions of abstracts for poster presentations are due by 21 January 2022; notifications will be provided by 22 February 2022. We strongly encourage potential attendees to submit an abstract as presenters have registration priority. For information about the conference, please refer to the main web page http://areadne.org or send email to us at info at areadne.org. We hope to see you at AREADNE 2022! Nicholas Hatsopoulos and John Pezaris, Co-Chairs AREADNE 2022 --- John S. Pezaris, Ph.D. AREADNE 2022 Co-Chair Harvard Medical School Massachusetts General Hospital 55 Fruit Street Boston, MA 02114, USA john at areadne.org From marinella.petrocchi at iit.cnr.it Tue Dec 7 11:05:55 2021 From: marinella.petrocchi at iit.cnr.it (Marinella Petrocchi) Date: Tue, 07 Dec 2021 17:05:55 +0100 Subject: Connectionists: [2nd CFP][ECIR 2022] ROMCIR 2022: The 2nd International Workshop on Reducing Online Misinformation through Credible Information Retrieval Message-ID: <8ab5b42cea596824dfa479080893dd9f@iit.cnr.it> [Apologies for multiple postings] ******************************************************************************************************************** ROMCIR 2022: The 2nd International Workshop on Reducing Online Misinformation through Credible Information Retrieval Stavanger, Norway, April 10, 2022 Conference website: https://romcir2022.disco.unimib.it/ Submission link: https://easychair.org/conferences/?conf=romcir2022 ******************************************************************************************************************** ***AIM AND THEMES*** Within the ECIR 2022 conference (https://ecir2022.org/), the second edition of the ROMCIR workshop is particularly focused on discussing and addressing issues related to reducing misinformation through Information Retrieval solutions. Hence, the central topic of the workshop concerns providing access to users to credible and/or verified information, to mitigate the information disorder phenomenon. By "information disorder" we mean all forms of communication pollution. From misinformation made out of ignorance, to intentional sharing of false content. In this context, all those approaches that can serve to the assessment of the credibility of information circulating online and in social media, in particular, find their place. This topic is very broad, as it concerns different contents (e.g., Web pages, news, reviews, medical information, online accounts, etc.), different Web and social media platforms (e.g., microblogging platforms, social networking services, social question-answering systems, etc.), and different purposes (e.g., identifying false information, accessing information based on its credibility, retrieving credible information, etc.). For this reason, the themes of interest include, but are not limited to, the following: - Access to credible information - Bias detection - Bot/Spam/Troll detection - Computational fact-checking - Crowdsourcing for credibility - Deep fakes - Disinformation/Misinformation detection - Evaluation strategies to assess information credibility - Fake news detection - Fake reviews detection - Filter Bubbles and Echo chambers - Harassment/bullying - Hate-speech detection - Information polarization in online communities - Propaganda identification/analysis - Retrieval of credible information - Security, privacy, and credibility - Sentiment/Emotional analysis - Stance detection - Trust and Reputation systems (to mitigate the effects of disinformation) - Understanding and guiding the societal reaction in the presence of disinformation Data-driven approaches in the IR field or related fields, supported by publicly available datasets, are more than welcome. ***CONTRIBUTIONS*** The workshop solicits the sending of two types of contributions relevant to the workshop and suitable to generate discussion: - Original, unpublished contributions (pre-prints submitted to ArXiv are eligible) that will be included in an open-access post-proceedings volume of CEUR Workshop Proceedings (http://ceur-ws.org/), indexed by both Scopus and DBLP. - Already published or preliminary work that will not be included in the post-proceedings volume. All submissions will undergo double-blind peer review by the program committee. Submissions are to be done electronically through the EasyChair at: https://easychair.org/conferences/?conf=romcir2022 ***SUBMISSION INSTRUCTIONS*** Submissions must be: - no more than 10 pages long (regular papers) - between 5 and 9 pages long (short papers) We recommend that authors use the new CEUR-ART style for writing papers to be published: - An Overleaf page for LaTeX users is available at: https://www.overleaf.com/read/gwhxnqcghhdt - An offline version with the style files including DOCX template files is available at: http://ceur-ws.org/Vol-XXX/CEURART.zip - The paper must contain, as the name of the conference: ROMCIR 2022: The 2nd Workshop on Reducing Online Misinformation through Credible Information Retrieval, held as part of ECIR 2022: the 44th European Conference on Information Retrieval, April 10-14, 2022, Stavanger, Norway - The title of the paper should follow the regular capitalization of English - Please, choose the single-column template - According to CEUR-WS policy, the papers will be published under a CC BY 4.0 license: https://creativecommons.org/licenses/by/4.0/deed.en If the paper is accepted, authors will be asked to sign (at pen) an author agreement with CEUR: - In case you do not employ Third-Party Material (TPM) in your draft, sign the document at http://ceur-ws.org/ceur-author-agreement-ccby-ntp.pdf?ver=2020-03-02 - If you do use TPM, the agreement can be found at http://ceur-ws.org/ceur-author-agreement-ccby-tp.pdf?ver=2020-03-02 Please submit an anonymized version of the submission (do not indicate the names of authors and institutions and cite your work in an impersonal way) ***IMPORTANT DATES*** - Abstract Submission Deadline: January 03, 2022 - Paper Submission Deadline: January 10, 2022 - Decision Notifications: February 11, 2022 - Workshop day: April 10, 2022 ***ORGANIZERS*** The following people contribute to the workshop in various capacities and roles: *Workshop Chairs* - Marinella Petrocchi (https://www.iit.cnr.it/en/marinella.petrocchi/), IIT-CNR, Pisa, Italy - Marco Viviani (https://ikr3.disco.unimib.it/people/marco-viviani/), University of Milano-Bicocca *Proceedings Chair* - Rishabh Upadhyay, University of Milano-Bicocca *Program Committee* - Rino Falcone, Institute of Cognitive Sciences and Technologies-CNR, Rome, Italy - Carlos A. Iglesias, Universidad Polit?cnica de Madrid, Madrid, Spain - Petr Knoth, The Open University, London, UK - Udo Kruschwitz, University of Regensburg, Regensburg, Germany - Yelena Mejova, ISI Foundation, Turin, Italy - Preslav Nakov, Qatar Computing Research Institute, HBKU, Doha, Qatar - Symeon Papadopoulos, Information Technologies Institute (ITI), Thessaloniki, Greece - Gabriella Pasi, University of Milano-Bicocca, Milan, Italy - Marinella Petrocchi, IIT ? CNR ? Istituto di Informatica e Telematica, Pisa, Italy - Adrian Popescu, CEA LIST, Gif-sur-Yvette, France - Paolo Rosso, Universitat Polit?cnica de Val?ncia, Val?ncia, Spain - Fabio Saracco, IMT School for Advanced Studies, Lucca, Italy - Marco Viviani, University of Milano-Bicocca, Milan, Italy - Xinyi Zhou, Syracuse University, Syracuse, NY, USA - Arkaitz Zubiaga, Queen Mary University of London, London, UK -- Marinella Petrocchi Senior Researcher @Institute of Informatics and Telematics (IIT) National Research Council (CNR) Pisa (Italy) Mobile: +39 348 8260773 Skype: m_arinell_a Web: https://marinellapetrocchi.wixsite.com/mysite `Luck is a matter of geography' (Bandabardo') From t.kosmala at qmul.ac.uk Tue Dec 7 11:35:52 2021 From: t.kosmala at qmul.ac.uk (Tomasz Kosmala) Date: Tue, 7 Dec 2021 16:35:52 +0000 Subject: Connectionists: Reinforcement Learning Challenge, 17th-31st January 2022 Message-ID: Reinforcement Learning Challenge, 17th-31st January 2022 The Net Zero Technology Centre, Alan Turing Institute RangL project and Oxquant announce the ?Pathways to Net Zero? Reinforcement Learning challenge, which will take place from 17th-31st January 2022. As showcased at COP26, the challenge is to control the rate of deployment of zero-carbon technologies towards net zero UK carbon emissions in 2050. Sign up to compete as an individual or team. More info: https://rangl.org/ COP26 video: https://vimeo.com/632748761 Challenge sign up form: https://docs.google.com/forms/d/e/1FAIpQLSdyFCd55fPasdq-30GQ1Hl4m_L5GgTULZ0WWO0GCLbiyKx8ag/viewform ---------------- Tomasz Kosmala School of Mathematical Sciences Queen Mary University of London t.kosmala at qmul.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Tue Dec 7 13:11:02 2021 From: terry at salk.edu (Terry Sejnowski) Date: Tue, 07 Dec 2021 10:11:02 -0800 Subject: Connectionists: NEURAL COMPUTATION - December 1, 2021 In-Reply-To: Message-ID: Neural Computation - Volume 33, Number 12 - December 1, 2021 available online for download now: http://www.mitpressjournals.org/toc/neco/33/12 http://cognet.mit.edu/content/neural-computation ----- Articles A Correspondence Between Normalization Strategies in Artificial and Biological Neural Networks Saket Navlakha, Yang Shen, and Julia Wang On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks Khashayar Filom, Roozbeh Farhoodi, and Konrad Paul Kording Letters Learning the Synaptic and Intrinsic Membrane Dynamics Underlying Working Memory in Spiking Neural Network Models Yinghao Li, Robert Kim, and Terrence J. Sejnowski Burster Reconstruction Considering Unmeasurable Variables in the Epileptor Model Jo?o Angelo Ferres Brogin, Jean Faber Ferreira de Abreu, and Douglas Domingues Bueno Simple Convolutional Based Models: Are They Learning the Task or the Data? Luis Sa-Couto, Andreas Wichert Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-associate Learning Sneha Aenugu, David E. Huber Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, and Masashi Sugiyama Bayesian Quadrature Optimization for Probability Threshold Robustness Measure Shogo Iwazaki, Yu Inatsu, and Ichiro Takeuchi ----- ON-LINE -- http://www.mitpressjournals.org/neco MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ----- From sandhyaprabhakaran at gmail.com Tue Dec 7 12:07:28 2021 From: sandhyaprabhakaran at gmail.com (Sandhya Prabhakaran) Date: Tue, 7 Dec 2021 12:07:28 -0500 Subject: Connectionists: CSBC/PS-ON Image analysis Hackathon (Feb 15th - 18th, 2022) Message-ID: Dear all, The Cancer Systems Biology Consortium (CSBC)/Physical Sciences in Oncology (PS-ON) will be holding a virtual Image Analysis Hackathon with multiple challenges from Feb 15-18th 2022. For registration and challenge descriptions, please go to: https://forms.gle/sCXoA6B4DkheUEJV9 Please consider participating! Regards, Sandhya Prabhakaran, PhD, (On behalf of the CSBC/PS-ON Image analysis working group) Moffitt Cancer Center, Florida http://sandhyaprabhakaran.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From lmuller2 at uwo.ca Tue Dec 7 22:57:28 2021 From: lmuller2 at uwo.ca (Lyle Muller) Date: Wed, 8 Dec 2021 03:57:28 +0000 Subject: Connectionists: Western-Fields Seminar Series | Jeannette Janssen Message-ID: <265FB9FE-024A-4FAD-89B2-C3772B6242D4@uwo.ca> The tenth talk in the 2021 Western-Fields Seminar Series in Networks, Random Graphs, and Neuroscience is Thursday 9 December at noon ET. Jeannette Janssen will give a talk titled ?Graphons as blueprints for spatial random graphs? (abstract below). Dr. Janssen is a Professor in the Department of Mathematics and Statistics at Dalhousie University. She has made fundamental contributions in graph theory, including the study of geometric graphs, spread of information on graphs, and infinite graphs. This seminar series has featured monthly virtual talks from a diverse group of researchers across computational neuroscience, physics, and graph theory. A summary and list of featured talks can be found at the series website. Registration link: https://www.fields.utoronto.ca/cgi-bin/register?form_selection=western-fields ? Given a compact measure space $S$, a graphon is a symmetric, measurable function $w:S\times S\rightarrow [0,1]$. A graphon corresponds in a natural way to a distribution on graphs. A graph can be sampled from this distribution by taking vertices $x_1,x_2,\dots ,x_n$ chosen u.a.r. from $S$, and then connecting each pair $x_i,x_j$ with probability $w(x_i,x_j)$ (conditionally independently). Graphons provide a very general framework to define spatial random graphs: let $S$ be a metric space, and let $w$ have the property that $w(x,y)$ decreases as $y$ moves further away from $x$, thus making links more likely between vertices that are closer together. I will start by discussing spatial graphons and the theory of graph limits, and then show (1) how the spatial layout of the graphon can be retrieved from the sampled graph (joint work with Aaron Smith) and (2) how graphons can provide a framework for signal processing on graphs sampled from the framework (joint work with Mahya Ghandehari and Nauzer Kalyaniwalla). -- Lyle Muller http://mullerlab.ca -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiaochun.cheng at gmail.com Wed Dec 8 03:59:58 2021 From: xiaochun.cheng at gmail.com (Xiaochun Cheng) Date: Wed, 8 Dec 2021 08:59:58 -0000 Subject: Connectionists: Call: Secure Smart Solutions for Organizational and End User Computing Message-ID: <009701d7ec11$fba1c0c0$f2e54240$@gmail.com> [Apologies for multiple postings] Special Issue title: Secure Smart Solutions for Organizational and End User Computing https://www.igi-global.com/calls-for-papers-special/journal-organizational-e nd-user-computing/1071 Submission Due Date 12/31/2021 -------------- next part -------------- An HTML attachment was scrubbed... URL: From helma.torkamaan at uni-due.de Thu Dec 9 02:46:17 2021 From: helma.torkamaan at uni-due.de (Helma Torkamaan) Date: Thu, 9 Dec 2021 08:46:17 +0100 Subject: Connectionists: ACM UMAP 2022 - Call for Papers Message-ID: <7d6377cf-17ee-794f-46c2-408ebac0cc54@uni-due.de> --- Please forward to anyone who might be interested --- --- Apologies for cross-posting --- -------------------------------------------------------- # **30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ?22)** Barcelona*, Spain, July 4?7, 2022 http://www.um.org/umap2022/ (*) Due to the ongoing COVID-19 pandemic, we are planning for a hybrid conference and will accommodate online presentations where needed. Submission Deadline: - Abstracts due:? February 10, 2022 (mandatory) - Full paper due: February 17, 2022 -------------------------------------------------------- **BACKGROUND AND SCOPE** ============================ **ACM UMAP** ? ***User Modeling, Adaptation and Personalization*** ? is the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users, and that collect, represent, and model user information. **ACM UMAP** is sponsored by ACM SIGCHI (https://sigchi.org) and SIGWEB (https://www.sigweb.org), and organized with User Modeling Inc. (https://um.org) as the core Steering Committee, extended with past years? chairs. The proceedings are published by the **ACM** and will be part of the ACM Digital Library (https://dl.acm.org). **ACM UMAP** covers a wide variety of research areas where personalization and adaptation may be applied. The main theme of **UMAP 2022** is ***?User control in personalized systems?***. Specifically, we welcome submissions related to user modeling, personalization, and adaptation in all areas of personalized systems, with an emphasis on how to balance adaptivity and user control. Below we present a short (but not prescriptive) list of topics of importance to the conference. ACM UMAP is co-located and collaborates with the ACM Hypertext conference (https://ht.acm.org/ht2022/). UMAP takes place one week after Hypertext, and uses the same submission dates and formats. We expect authors to submit research on personalized systems to UMAP and invite authors to submit their Web-related work without a focus on personalization to the Hypertext conference. The two conferences will organize one shared track on **personalized recommender systems** (same track chairs and PC, see the track description). -------------------------------------------------------- ?**IMPORTANT DATES** ============================ - Paper Abstracts:?? February 10, 2022 (mandatory) - Full paper:???????????? February 17, 2022 - Notification:?????????? April 11, 2022 - Conference:????????? July 4-July 7, 2022 **Note**: The submissions deadlines are at 11:59pm AoE time (Anywhere on Earth) -------------------------------------------------------- ?**CONFERENCE TOPICS** ?============================ We welcome submissions related to *user modeling, personalization, and adaptation in any area*. The topics listed below are not intended to limit possible contributions. **Detailed descriptions and the suggested topics for each track are reported in the online version of the CFP on the UMAP 2022 web site.** ### **Personalized Recommender Systems*** **Track Chairs: Osnat Mokryn (University of Haifa), Eva Zangerle (University of Innsbruck, Austria) and Markus Zanker (University of Bolzano, Italy, and University of Klagenfurt, Austria)** (*) This is a joint track between ACM UMAP and ACM Hypertext (same track chairs, overlapping PC). Authors planning to contribute to this track can submit to either conference, depending on their broader interest in either Hypertext or UMAP. Track chairs organize a special issue in the journal New Review of Hypermedia and Multimedia. This track aims to provide a forum for researchers and practitioners to discuss open challenges, latest solutions and novel research approaches in the field of recommender systems. In addition to mature research works addressing technical aspects pertaining to recommendations, we also particularly welcome research contributions that address questions related to the user perception and the business value of recommender systems. ### **Adaptive Hypermedia, Semantic, and Social Web** **Track Chairs: Alexandra I. Cristea (Durham University, UK) and Peter Brusilovsky (University of Pittsburgh, US)** This track aims to provide a forum to researchers to discuss open research problems, solid solutions, latest challenges, novel applications, and innovative research approaches in adaptive hypermedia, semantic and social web. We invite original submissions addressing all aspects of personalization, user models building, and personal experience in online social systems. ### **Intelligent User Interfaces** **Track chairs: Elisabeth Lex (Graz University of Technology, Austria) and Marko Tkalcic (University of Primorska, Slovenia)** This topic can be characterized by exploring how to make the interaction between computers and people smarter and more productive, which may leverage solutions from human-computer interaction, data mining, natural language processing, information visualization, and knowledge representation and reasoning. ### **Technology-Enhanced Adaptive Learning** **Track chairs: Judy Kay (University of Sydney, Australia) and Sharon Hsiao (Santa Clara University, US)** This track invites researchers, developers, and practitioners from various disciplines to present their innovative learning solutions, share acquired experience, and discuss their modeling challenges for personalized adaptive learning. ### **Fairness, Transparency, Accountability, and Privacy** **Track chairs: Bamshad Mobasher (DePaul University College of Computing and Digital Media, US) and Munindar P. Singh (NC State University, US)** Adaptive systems researchers and developers have a social responsibility to care about the impact of their technologies on individual people (users, providers, and other stakeholders) and on society. This track invites work that pertains to the science of building, maintaining, evaluating, and studying adaptive systems that are fair, transparent, respectful of users? privacy, and beneficial to society. ### **Personalization for Persuasive and Behavior Change Systems** **Track chairs: Julita Vassileva (University of Saskatchewan, Canada) and Panagiotis Germanakos (SAP SE, Germany)** This track invites original submissions addressing the areas of personalization and tailoring for persuasive technologies, including but not limited to personalization models, user models, computational personalization, design and evaluation methods, and personal experience designing personalized and adaptive behaviour change technologies. ### **Virtual Assistants and Personalized Human-robot Interaction** **Track chairs: Radhika Garg (Syracuse University, US) and Cristina Gena (University of Torino, Italy)** This track aims at investigating new models and techniques for the adaptation of synthetic companions (e.g., virtual assistants, chatbots, social robots) to the individual user. ### **Research Methods and Reproducibility** **Track chairs: Odd Erik Gundersen (Norwegian University of Science and Technology, Norway) and Dietmar Jannach (University of Klagenfurt, Austria)** This track accepts works on methodologies for the evaluation of personalized systems, benchmarks, measurement scales, with particular attention to reproducibility of results and of techniques. -------------------------------------------------------- ?**SUBMISSION AND REVIEW PROCESS** ?============================ Please consult the conference website for the submission link: http://www.um.org/umap2022/. The maximum length is **14 pages (excluding references) in the ACM new single-column format**. We encourage papers of any length up to 14 pages; reviewers will be asked to comment on whether the length is appropriate for the contribution. **Additional review criteria are available in the online version of the CFP on the UMAP 2022 web site.** Each accepted paper will be included in the conference proceedings and presented at the conference. UMAP uses a **double blind** review process. Authors must omit their names and affiliations from submissions, and avoid obvious identifying statements. For instance, citations to the authors' own prior work should be made in the third person. Failure to anonymize your submission results in the desk-rejection of your paper. -------------------------------------------------------- **ORGANIZERS** ============================ **General chairs** - Ludovico Boratto, University of Cagliari, Italy - Alejandro Bellog?n, Universidad Aut?noma de Madrid, Spain - Olga C. Santos, Spanish National University for Distance Education, Spain **Program Chairs** - Liliana Ardissono, University of Torino, Italy - Bart Knijnenburg, Clemson University, US -------------------------------------------------------- **RELATED EVENTS** ============================ Separate calls will be sent for Workshops and Tutorials, Doctoral Consortium, and Demo/Late-Breaking Results, as these have different deadlines and submission requirements. -- Helma Torkamaan Researcher University of Duisburg-Essen Interactive Systems Group Room LF 288, Forsthausweg 2, 47057 Duisburg, GERMANY helma.torkamaan at uni-due.de / +49 203 379-2276 -------------- next part -------------- An HTML attachment was scrubbed... URL: From snooles at gmail.com Wed Dec 8 07:39:18 2021 From: snooles at gmail.com (Gilles Vanwalleghem) Date: Wed, 8 Dec 2021 13:39:18 +0100 Subject: Connectionists: Postdoc position working on the gut-brain axis in Aarhus - Denmark Message-ID: I am hiring a postdoc for my new lab to study the enteric nervous system of Zebrafish in a brand new building and lab. Light-sheet microscopy, brain imaging, microbes! The position is 2 years, with possibility of extension. The start date would be March or April 2022. The job position is described here: https://mbg.au.dk/en/news-and-events/vacancies/job/postdoc-position-in-neurobiology Information on my research can be found here: https://mbg.au.dk/en/gilles-vanwalleghem Best regards, Gilles Vanwalleghem Assistant Professor in neurobiology Department of Molecular Biology and Genetics Aarhus University Denmark -------------- next part -------------- An HTML attachment was scrubbed... URL: From jpezaris at gmail.com Wed Dec 8 12:08:56 2021 From: jpezaris at gmail.com (John Pezaris) Date: Wed, 8 Dec 2021 12:08:56 -0500 Subject: Connectionists: AREADNE 2022 Call for Abstracts Message-ID: AREADNE 2022 Research in Encoding and Decoding of Neural Ensembles Nomikos Conference Centre, Santorini, Greece 28 June - 2 July 2022 http://areadne.org info at areadne.org Dear Colleague, We are pleased to announce solicitation of abstracts for poster presentation at AREADNE 2022, 28 June - 2 July 2022, our ninth meeting to be held at the Nomikos Conference Centre in Santorini, Greece. Continuing with the same highly successful format, AREADNE 2022 will bring scientific leaders from around the world to present their theoretical and experimental work on the functioning of neuronal ensembles. The meeting will provide an informal yet spectacular setting in which attendees can discuss their recent ideas and discoveries, with a relaxed pace that emphasizes interaction. Please see the Call for Abstracts for additional details, including links for templates, at http://areadne.org/call-for-abstracts Submissions of abstracts for poster presentations are due by 21 January 2022; notifications will be provided by 22 February 2022. We strongly encourage potential attendees to submit an abstract as presenters have registration priority. For information about the conference, please refer to the main web page http://areadne.org or send email to us at info at areadne.org. We hope to see you at AREADNE 2022! Nicholas Hatsopoulos and John Pezaris, Co-Chairs AREADNE 2022 --- John S. Pezaris, Ph.D. AREADNE 2022 Co-Chair Harvard Medical School Massachusetts General Hospital 55 Fruit Street Boston, MA 02114, USA john at areadne.org From J.Spencer at uea.ac.uk Thu Dec 9 13:11:06 2021 From: J.Spencer at uea.ac.uk (John Spencer (PSY - Staff)) Date: Thu, 9 Dec 2021 18:11:06 +0000 Subject: Connectionists: Post-doctoral posts in England / Germany... In-Reply-To: References: Message-ID: <23BECB6A-FA31-4584-B363-A0B4D67DF74B@uea.ac.uk> Please circulate the info below to any talented candidates. Three year postdoctoral positions in England / Germany Profs. John Spencer and Gregor Schoener are looking for two postdoctoral candidates to work on a joint project funded by the Leverhulme Trust. The goal of the project is to construct a theory that explains how the brain flexibly integrates lower-level processes with higher-level language and executive functions. The project will use the framework of Dynamic Field Theory (www.dynamicfieldtheory.org) to both simulate human behaviours and embody the theory on an autonomous robot to explore application to real-world scenarios. One postdoctoral fellow will be housed in the School of Psychology at the University of East Anglia in Norwich, UK. The other fellow will be housed at the Institute for Neurocomputing at the Ruhr University in Bochum, Germany. Inquiries can be addressed to John Spencer (j.spencer at uea.ac.uk) or Gregor Schoener (gregor.schoener at ini.rub.de). Applications are due by January 20, 2022. The posts will be available starting March 7, 2022. John P. Spencer, PhD Professor Developmental Dynamics Lab https://www.facebook.com/DDPSYUEA http://www.uea.ac.uk/developmental-dynamics-lab/home School of Psychology, Room 0.09 Lawrence Stenhouse Building, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ United Kingdom Telephone 01603 593968 [/var/folders/jl/_9mpm6j92_9ckmg0q9qhs4986d96kt/T/com.microsoft.Outlook/WebArchiveCopyPasteTempFiles/cidimage002.jpg at 01D48BB4.171FA130][/var/folders/jl/_9mpm6j92_9ckmg0q9qhs4986d96kt/T/com.microsoft.Outlook/WebArchiveCopyPasteTempFiles/cidimage004.jpg at 01D48BB4.171FA130] Gold (Teaching Excellence Framework 2017-2021) World Top 200 (Times Higher Education World University Rankings 2020) UK Top 25 (The Times/Sunday Times 2020 and Complete University Guide 2020) World Top 50 for research citations (Times Higher Education World University Rankings 2020) Athena SWAN Silver Award Holder in recognition of advancement of gender equality for all (Advance HE 2019) Any personal data exchanged as part of this email conversation will be processed by the University in accordance with current UK data protection law and in line with the relevant UEA Privacy Notice. This email is confidential and may be privileged. If you are not the intended recipient please accept my apologies; please do not disclose, copy or distribute information in this email or take any action in reliance on its contents: to do so is strictly prohibited and may be unlawful. Please inform me that this message has gone astray before deleting it. Thank you for your co-operation. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 198 bytes Desc: image001.png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.jpg Type: image/jpeg Size: 5591 bytes Desc: image002.jpg URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image003.jpg Type: image/jpeg Size: 2464 bytes Desc: image003.jpg URL: From haim.dub at gmail.com Thu Dec 9 11:02:52 2021 From: haim.dub at gmail.com (dubossarsky haim) Date: Thu, 9 Dec 2021 16:02:52 +0000 Subject: Connectionists: CfP: 3rd International Workshop on Computational Approaches to Historical Language Change 2022 Message-ID: First call for Papers 3rd International Workshop on Computational Approaches to Historical Language Change 2022 (LChange?22) Contact email: PC-ACLws2022 at languagechange.org Website: https://languagechange.org/events/2022-acl-lchange/ Workshop description Just like the first two workshops, the third LChange workshop will be co-located with ACL (2022) to be held in Dublin, during May 26-28, 2022 (exact dates will be announced later) and will be a hybrid event with the possibility of online participation (following the main conference). This workshop explores state-of-the-art computational methodologies, theories and digital text resources on exploring the time-varying nature of human language. The aim of this workshop is to provide pioneering researchers who work on computational methods, evaluation, and large-scale modelling of language change an outlet for disseminating cutting-edge research on topics concerning language change. Besides these goals, this workshop will also support discussion on the evaluation of computational methodologies for uncovering language change. This year, LChange will feature a shared task on semantic change detection for Spanish as one track of the workshop. Timeline for the shared task will be released shortly. This year we will offer mentoring for PhD students and young researchers in one-on-one meetings during the workshop. If you are interested, send us a short description of your work and we will set you up with one of the organizers of this workshop. If your paper is rejected from the workshop, we can also provide advice on improving it for future submission. This offer is limited, and will be chosen based on topical fit and availability of appropriate mentors. Deadline for applying for mentorship is May 30th via . Via our sponsor, Iguanadon.ai, we can offer one free registration for a PhD student! Apply by emailing us your short cv and why you need your registration paid. Important Dates * February 28, 2022: Paper submission * March 26, 2022: Notification of acceptance * March 30, 2022: Deadline for mentorship application * April 10, 2022: Camera-ready papers due * May 26-28, 2022: Workshop date (days will be decided upon later) Keynote Talks There will be two keynote talks providing us with different perspectives, both methods, application and evaluation. These will be announced in the next few months. Submissions We accept three types of submissions, long papers and short papers and task description papers for the shared task track, all following the ACL2021 style, and the ACL submission policy: https://www.aclweb.org/adminwiki/index.php?title=ACL_Policies_for_Submission,_Review_and_Citation Long papers may consist of up to eight (8) pages of content, plus unlimited references, short papers may consist of up to four (4) pages of content; final versions will be given one additional page of content so that reviewers' comments can be taken into account. Abstracts may consist of up to two (2) pages of content, plus unlimited references but will not be given any additional page upon acceptance. Submissions should be sent in electronic forms, using the Softconf START conference management system. The submission site will be announced on the workshop page https://languagechange.org/events/2022-acl-lchange/ once available. We invite original research papers from a wide range of topics, including but not limited to: * Novel methods for detecting diachronic semantic change and lexical replacement * Automatic discovery and quantitative evaluation of laws of language change * Computational theories and generative models of language change * Sense-aware (semantic) change analysis * Diachronic word sense disambiguation * Novel methods for diachronic analysis of low-resource languages * Novel methods for diachronic linguistic data visualization * Novel applications and implications of language change detection * Quantification of sociocultural influences on language change * Cross-linguistic, phylogenetic, and developmental approaches to language change * Novel datasets for cross-linguistic and diachronic analyses of language Submissions are open to all, and are to be submitted anonymously. All papers will be refereed through a double-blind peer review process by at least three reviewers with final acceptance decisions made by the workshop organizers. The workshop is scheduled to last for two days during May 26th and 28th (with exact dates announced later). Contact us at PC-ACLws2022 at languagechange.org if you have any questions. Workshop organizers: Nina Tahmasebi, University of Gothenburg Lars Borin, University of Gothenburg Simon Hengchen, University of Gothenburg Syrielle Montariol, University Paris-Saclay Haim Dubossarsky, Queen Mary University of London Andrey Kutuzov, University of Oslo -------------- next part -------------- An HTML attachment was scrubbed... URL: From jkummerf at umich.edu Thu Dec 9 16:56:55 2021 From: jkummerf at umich.edu (Jonathan Kummerfeld) Date: Thu, 9 Dec 2021 16:56:55 -0500 Subject: Connectionists: Openings in the PhD program at the University of Sydney in NLP Message-ID: I'm recruiting PhD students for my new group at the University of Sydney. See this page for details: https://www.jkk.name/students/recruiting-phd/ The deadline to apply is *December 17, 2021*. The start date can either be in late 2022 or early 2023. Note that, unlike the central application process for many PhD programs, students should apply directly to me. Thanks! Jonathan Kummerfeld -- Visiting Scholar, Harvard University Research Associate II, University of Michigan Mid-2022: Senior Lecturer (ie. research tenure-track Asst. Prof.) U. Sydney e: jkummerf at umich.edu w: www.jkk.name -------------- next part -------------- An HTML attachment was scrubbed... URL: From arminmustafa at gmail.com Fri Dec 10 05:19:27 2021 From: arminmustafa at gmail.com (armin mustafa) Date: Fri, 10 Dec 2021 10:19:27 +0000 Subject: Connectionists: [Job] - Research Fellow/Senior Research Fellow in Computer Vision, Spatial Audio and Audio-Visual AI Message-ID: Could you please circulate this call? Research Fellow/Senior Research Fellow in Computer Vision, Spatial Audio and Audio-Visual AIVision, Speech & Signal Processing Location: Guildford Salary: ?33,309 to ?50,296 per annum Fixed Term Post Type: Full Time Closing Date: 23.59 hours GMT on Friday 17 December 2021 Reference: 073621 Join a new research partnership with the BBC at the Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey. More details here: https://jobs.surrey.ac.uk/vacancy.aspx?ref=073621 How to apply Informal enquiries are welcomed by Professor Adrian Hilton by email ( a.hilton at surrey.ac.uk) or via the University of Surrey jobs website https://jobs.surrey.ac.uk/Vacancies.aspx Many Thanks, Armin Mustafa -------------- next part -------------- An HTML attachment was scrubbed... URL: From a.pucyk at icm.edu.pl Fri Dec 10 06:18:06 2021 From: a.pucyk at icm.edu.pl (Alicja Pucyk) Date: Fri, 10 Dec 2021 12:18:06 +0100 Subject: Connectionists: =?iso-8859-2?q?Free_Virtual_ICM_Seminar_with_prof?= =?iso-8859-2?q?=2E_Wies=B3aw_Nowi=F1ski-_creator_of_=22world=27s_m?= =?iso-8859-2?q?ost_gorgeous=22_human_brain_atlases_=7C_Dec_16=2C_4?= =?iso-8859-2?q?pm_CET?= Message-ID: <121301d7edb7$9b5388a0$d1fa99e0$@icm.edu.pl> "Life is too short to do anything else than to study the human brain, and to prevent or cure its 1,000 disorders."- Wies?aw Nowi?ski ========================================================= XX Virtual ICM Seminar with Wies?aw Nowi?ski [Cardinal Stefan Wyszy?ski University in Warsaw, Poland] ========================================================= ___ Interdisciplinary Centre for Mathematical and Computational Modelling - ICM University of Warsaw gathers outstanding scientists in a series of Virtual ICM Seminars. With XIX meetings so far and more than 1500 participants, ICM invites everyone to join its next seminar. TITLE: Human brain atlases and their applications DATE: Thursday, December 16, 2021 | 4pm CST FREE registration: https://supercomputingfrontiers.eu/2021/seminars/ ICM University of Warsaw is proud to invite everyone to #VirtualICMSeminar with scientist, innovator, entrepreneur, pioneer and visionary Prof. Wieslaw Nowinski- creator of "world's most gorgeous" human brain atlases! During the seminar, prof. Nowi?ski will share his experience in brain atlas creation and the development of atlas-enabled applications for neuroeducation, brain research, neurology, stroke, psychiatry, neuroradiology, and neurosurgery for deep brain stimulation. Don't miss it! Register NOW. _Abstract The 21st century is the century of the brain and mind, and to gather, present, use, and discover knowledge about the brain, the brain atlases are employed. A recent tremendous brain atlas development in terms of content, functionality and applications has additionally been propelled by brain big projects. Prof. Wies?aw Nowi?ski has created diverse human brain atlases, including research prototypes and 35 products licensed to 67 companies and institutions, and distributed in about 100 countries. These are anatomic, vascular, connectomic, functional and population-based atlases in health and disease. Wies?aw Nowi?ski will share his experience in brain atlas creation and the development of atlas-enabled applications for neuroeducation (including a family of The Human Brain in 1492/1969/2953 Pieces atlases and the NOWinBRAIN brain image repository), brain research, neurology (3D Atlas of Neurologic Disorders), stroke (atlas-assisted decision making, diagnosis support in emergency room, and probabilistic stroke atlas for prediction), psychiatry, neuroradiology, and neurosurgery for deep brain stimulation. _BIO Prof. Wieslaw L. Nowinski, D.Sc., Ph.D. - scientist, innovator, entrepreneur, pioneer and visionary; science-medicine-art "bridge builder"; creator of "world's most gorgeous" human brain atlases. Affiliated with the world's top universities in the USA, China and Singapore, No 2 in MED and No 2, 6, 9 in ENG (Shanghai ranking). He has 580 scientific publications (h-index 48, i10-index 178 (Google Scholar), within world's top 2% scientists (Stanford list)); 71 patents granted (23 US, 11 EP) and 68 patent applications filed (19 US, 21 EP). Created with his team 35 brain atlas products licensed to 67 companies and institutions, distributed in about 100 countries. Conferred with 45 awards, 30 from leading medical societies (two radiological Oscars, Pioneer in Medicine) and 3 for innovation (2014 European Inventor of the Year (within the top three)); named The Outstanding Pole in the world in 2012. Commemorated on a stamp issued by the Polish Post in 2018 to honor Polish inventors of the century (within two living inventors). Best regards, Alicja Pucyk Event Manager --- Interdisciplinary Centre for Mathematical and Computational Modelling University of Warsaw a.pucyk at icm.edu.pl www.icm.edu.pl/en/ www.supercomputingfrontiers.eu From R.Borisyuk at plymouth.ac.uk Fri Dec 10 09:44:28 2021 From: R.Borisyuk at plymouth.ac.uk (Roman Borisyuk) Date: Fri, 10 Dec 2021 14:44:28 +0000 Subject: Connectionists: Postdoctoral position in Computational Neuroscience at the University of Exeter, UK Message-ID: A Postdoctoral Research Fellow 2 year?s position in Computational Neuroscience is available at the Department of Mathematics, University of Exeter, UK to work on a BBSRC-funded project, in collaboration with neurobiologists from the University of St Andrews. Vertebrate neural circuits can dynamically change their activity to generate an appropriate behaviour in response to a changing environment. This project asks how neural networks can switch between different behaviours. Specifically, you will investigate the dynamic transitions between two rhythmic activity patterns in the spinal circuits of the frog tadpole to discover the cellular and network mechanisms driving this transition. You will build and simulate biologically realistic models of neural activity from population to conductance-based level as well as probabilistic models of connectivity (Roberts et al., J Neurosci 2014; Borisyuk et al., PLOS One 2014; Ferrario et al., eLife 2018, PLOS Comp Biology 2021). Familiarity with nonlinear dynamics of neural activity and strong code writing skills (in languages such as C++, Python and MATLAB) are expected. You will be supported by experimental collaborators who have determined neuronal and network properties with an exquisite level of detail. Predictions from your simulations will be tested experimentally using an array of electrophysiology and imaging tools. Fundamental neuronal mechanisms are highly conserved across vertebrate species, so your results will provide insight on dynamic circuit reconfiguration in more complex neural networks in mammals. The University of Exeter provides a vibrant environment for multidisciplinary studies. This is facilitated by the newly built Living Systems Institute, which promotes collaborations between mathematicians, computer scientists and neuroscientists. Exeter is a mid-sized city in the South West of England, just a few miles from the beautiful Jurassic coast and wild moor lands. For more information about this job and to apply, please follow the link http://bit.ly/ResearchFellowExeter Enquiries: Dr Joel Tabak j.tabak at exeter.ac.uk Prof Roman Borisyuk r.m.borisyuk at exeter.ac.uk ________________________________ [http://www.plymouth.ac.uk/images/email_footer.gif] This email and any files with it are confidential and intended solely for the use of the recipient to whom it is addressed. If you are not the intended recipient then copying, distribution or other use of the information contained is strictly prohibited and you should not rely on it. If you have received this email in error please let the sender know immediately and delete it from your system(s). Internet emails are not necessarily secure. While we take every care, University of Plymouth accepts no responsibility for viruses and it is your responsibility to scan emails and their attachments. University of Plymouth does not accept responsibility for any changes made after it was sent. Nothing in this email or its attachments constitutes an order for goods or services unless accompanied by an official order form. -------------- next part -------------- An HTML attachment was scrubbed... URL: From schockaerts1 at cardiff.ac.uk Fri Dec 10 10:20:11 2021 From: schockaerts1 at cardiff.ac.uk (Steven Schockaert) Date: Fri, 10 Dec 2021 15:20:11 +0000 Subject: Connectionists: Postdoctoral position at Cardiff University Message-ID: Location: Cardiff, UK Deadline for applications: 5th January 2022 Start date: 1st May 2022 (or as soon as possible thereafter) Duration: 30 months Keywords: natural language processing, representation learning, commonsense reasoning Details about the post Applications are invited for a postdoctoral research associate post to work on the EPSRC Open Fellowship project ReStoRe (Reasoning about Structured Story Representations), which is focused on story-level language understanding. The aim of this post is to develop methods for learning graph-structured representations of stories, where nodes correspond to entities and events, and edges indicate relationships. More specifically, the focus will be on learning sparse and interpretable vector representations of these entities, events and relationships. These vector representations will then form the basis for implementing common sense reasoning strategies, allowing us to fill the gap between what is explicitly stated in a story and what a human reader would infer by ?reading between the lines?. More details about the post and instructions on how to apply are available here: https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=30011&siteid=5460&PageType=JobDetails&jobid=1897761 Background about the ReStoRe project When we read a story as a human, we build up a mental model of what is described. Such mental models are crucial for reading comprehension. They allow us to relate the story to our earlier experiences, to make inferences that require combining information from different sentences, and to interpret ambiguous sentences correctly. Crucially, mental models capture more information than what is literally mentioned in the story. They are representations of the situations that are described, rather than the text itself, and they are constructed by combining the story text with our commonsense understanding of how the world works. The field of Natural Language Processing (NLP) has made rapid progress in the last few years, but the focus has largely been on sentence-level representations. Stories, such as news articles, social media posts or medical case reports, are essentially modelled as collections of sentences. As a result, current systems struggle with the ambiguity of language, since the correct interpretation of a word or sentence can often only be inferred by taking its broader story context into account. They are also severely limited in their ability to solve problems where information from different sentences needs to be combined. As a final example, current systems struggle to identify correspondences between related stories (e.g. different news articles about the same event), especially if they are written from a different perspective. To address these fundamental challenges, we need a method to learn story-level representations that can act as an analogue to mental models. Intuitively, there are two steps involved in learning such story representations: first we need to model what is literally mentioned in the story, and then we need some form of commonsense reasoning to fill in the gaps. In practice, however, these two steps are closely interrelated: interpreting what is mentioned in the story requires a model of the story context, but constructing this model requires an interpretation of what is mentioned. The solution that is proposed in this fellowship is based on representations called story graphs. These story graphs encode the events that occur, the entities involved, and the relationships that hold between these entities and events. A story can then be viewed as an incomplete specification of a story graph, similar to how a symbolic knowledge base corresponds to an incomplete specification of a possible world. The proposed framework will allow us to reason about textual information in a principled way. It will lead to significant improvements in NLP tasks where a commonsense understanding is required of the situations that are described, or where information from multiple sentences or documents needs to be combined. It will furthermore enable a step change in applications that directly rely on structured text representations, such as situational understanding, information retrieval systems for the legal, medical and news domains, and tools for inferring business insights from news stories and social media feeds. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Donald.Adjeroh at mail.wvu.edu Fri Dec 10 11:37:10 2021 From: Donald.Adjeroh at mail.wvu.edu (Donald Adjeroh) Date: Fri, 10 Dec 2021 16:37:10 +0000 Subject: Connectionists: Post-doctoral Fellows -- Computer Vision, AI, and Digital Health at WVU Message-ID: We have openings at the Lane Department of Computer Science and Electrical Engineering, West Virginia University (WVU) for post-doctoral positions in computer vision, AI, with applications in digital health. We are looking for candidates with a strong background in computer vision, deep learning, applied mathematics, and biomedical image analysis, especially ultrasound images. The focus will be on developing new algorithms and techniques that use advances in AI and machine learning to analyze different types of biomedical data. We have significant interest on cardiovascular health (especially on the analysis of cardiac images, such as echocardiographs, MRI, CT images, etc.), health disinformation, trust, and privacy preserving health data analytics. Please check any of the links below for more details: https://wvu.taleo.net/careersection/faculty/jobdetail.ftl?job=18208&lang=en or https://jobs.chronicle.com/job/403664/postdoctoral-fellow-lane-department-of-computer-science-and-electrical-engineering-statler Don Adjeroh, PhD Professor and Associate Chair Graduate Coordinator of Computer Science West Virginia University Morgantown, WV 26506 http://community.wvu.edu/~daadjeroh/ Tel: 304-293-9681 Fax: 304-293-8602 -------------- next part -------------- An HTML attachment was scrubbed... URL: From calendarsites at insticc.org Fri Dec 10 13:17:47 2021 From: calendarsites at insticc.org (calendarsites at insticc.org) Date: Fri, 10 Dec 2021 18:17:47 -0000 Subject: Connectionists: [CFP] 2nd Int. Conf. on Image Processing and Vision Engineering :: Submission Deadline Approaching Message-ID: <004b01d7edf2$3d2f0840$b78d18c0$@insticc.org> CALL FOR PAPERS 2nd International Conference on Image Processing and Vision Engineering **Submission Deadline: December 21, 2021** https://improve.scitevents.org/ April 22 - 24, 2022 Online Streaming Dear Colleagues, We would be very pleased to receive a regular or a position paper from you, with recent results, to be presented at IMPROVE 2022 until the 21st December 2021. This would be a nice opportunity for you to join this community and take advantage of our low registration fees since the conference will be entirely online. IMPROVE is a comprehensive conference of academic and technical nature, focused on image processing and computer vision practical applications. It brings together researchers, engineers and practitioners working either in fundamental areas of image processing, developing new methods and techniques, including innovative machine learning approaches, as well as multimedia communications technology and applications of image processing and artificial vision in diverse areas. Conference Chair Sebastiano Battiato, University of Catania, Italy Program Chair(s) Francisco Imai, Apple Inc., United States Cosimo Distante, CNR, Italy With the presence of internationally distinguished keynote speakers: Jiri Matas, Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic Michael Bronstein, Imperial College London, United Kingdom Ren? Vidal, The Johns Hopkins University, United States Proceedings will be submitted for indexation by: SCOPUS, Google Scholar, The DBLP Computer Science Bibliography, Semantic Scholar, Microsoft Academic, Engineering Index (EI), Web of Science / Conference Proceedings Citation Index. A short list of presented papers will be invited for a post-conference special issue of the Springer Nature Computer Science journal. All papers presented at the conference venue will also be available at the SCITEPRESS Digital Library. Kind regards, Monica Saramago IMPROVE Secretariat Web: http://improve.scitevents.org e-mail: improve.secretariat at insticc.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From calendarsites at insticc.org Fri Dec 10 13:17:47 2021 From: calendarsites at insticc.org (calendarsites at insticc.org) Date: Fri, 10 Dec 2021 18:17:47 -0000 Subject: Connectionists: [CFP] 2nd Int. Conf. on Image Processing and Vision Engineering :: Submission Deadline Approaching Message-ID: <005001d7edf2$3dd9c730$b98d5590$@insticc.org> CALL FOR PAPERS 2nd International Conference on Image Processing and Vision Engineering **Submission Deadline: December 21, 2021** https://improve.scitevents.org/ April 22 - 24, 2022 Online Streaming Dear Colleagues, We would be very pleased to receive a regular or a position paper from you, with recent results, to be presented at IMPROVE 2022 until the 21st December 2021. This would be a nice opportunity for you to join this community and take advantage of our low registration fees since the conference will be entirely online. IMPROVE is a comprehensive conference of academic and technical nature, focused on image processing and computer vision practical applications. It brings together researchers, engineers and practitioners working either in fundamental areas of image processing, developing new methods and techniques, including innovative machine learning approaches, as well as multimedia communications technology and applications of image processing and artificial vision in diverse areas. Conference Chair Sebastiano Battiato, University of Catania, Italy Program Chair(s) Francisco Imai, Apple Inc., United States Cosimo Distante, CNR, Italy With the presence of internationally distinguished keynote speakers: Jiri Matas, Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic Michael Bronstein, Imperial College London, United Kingdom Ren? Vidal, The Johns Hopkins University, United States Proceedings will be submitted for indexation by: SCOPUS, Google Scholar, The DBLP Computer Science Bibliography, Semantic Scholar, Microsoft Academic, Engineering Index (EI), Web of Science / Conference Proceedings Citation Index. A short list of presented papers will be invited for a post-conference special issue of the Springer Nature Computer Science journal. All papers presented at the conference venue will also be available at the SCITEPRESS Digital Library. Kind regards, Monica Saramago IMPROVE Secretariat Web: http://improve.scitevents.org e-mail: improve.secretariat at insticc.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From oliver at roesler.co.uk Fri Dec 10 11:52:06 2021 From: oliver at roesler.co.uk (Oliver Roesler) Date: Fri, 10 Dec 2021 16:52:06 +0000 Subject: Connectionists: CFP Special Issue on Socially Acceptable Robot Behavior: Approaches for Learning, Adaptation and Evaluation Message-ID: <8026add8-2892-a973-8a0f-4a593f868106@roesler.co.uk> *CALL FOR PAPERS* **Apologies for cross-posting** *Special Issue* on *Socially Acceptable Robot Behavior: Approaches for Learning, Adaptation and Evaluation* in Interaction Studies *I. Aim and Scope* A key factor for the acceptance of robots as regular partners in human-centered environments is the appropriateness and predictability of their behavior. The behavior of human-human interactions is governed by customary rules that define how people should behave in different situations, thereby governing their expectations. Socially compliant behavior is usually rewarded by group acceptance, while non-compliant behavior might have consequences including isolation from a social group. Making robots able to understand human social norms allows for improving the naturalness and effectiveness of human-robot interaction and collaboration. Since social norms can differ greatly between different cultures and social groups, it is essential that robots are able to learn and adapt their behavior based on feedback and observations from the environment. This special issue in Interaction Studies aims to attract the latest research aiming at learning, producing, and evaluating human-aware robot behavior, thereby, following the recent RO-MAN 2021 Workshop on Robot Behavior Adaptation to Human Social Norms (TSAR) in providing a venue to discuss the limitations of the current approaches and future directions towards intelligent human-aware robot behaviors. *II. Submission* 1. Before submitting, please check the official journal guidelines . 2. For paper submission, please use the online submission system . 3. After logging into the submission system, please click on "Submit a manuscript" and select "Original article". 4. Please ensure that you select "Special Issue: Socially Acceptable Robot Behavior" under "General information". ??? The primary list of topics covers the following points (but not limited to): * Human-human vs human-robot social norms * Influence of cultural and social background on robot behavior perception * Learning of socially accepted behavior * Behavior adaptation based on social feedback * Transfer learning of social norms experience * The role of robot appearance on applied social norms * Perception of socially normative robot behavior * Human-aware collaboration and navigation * Social norms and trust in human-robot interaction * Representation and modeling techniques for social norms * Metrics and evaluation criteria for socially compliant robot behavior *III. Timeline* 1. Deadline for paper submission: *January 31, 2022*** 2. First notification for authors: *April 15, 2022* 3. Deadline for revised papers submission: *May 31, 2022* 4. Final notification for authors: *July 15, 2022* 5. Deadline for submission of camera-ready manuscripts: *August 15, 2022* ??? Please note that these deadlines are only indicative and that all submitted papers will be reviewed as soon as they are received. *IV. Guest Editors* 1. *Oliver Roesler* ? Vrije Universiteit Brussel ? Belgium 2. *Elahe Bagheri* ? Vrije Universiteit Brussel ? Belgium 3. *Amir Aly* ? University of Plymouth ? UK 4. *Silvia Rossi* ? University of Naples Federico II ? Italy 5. *Rachid Alami* ? CNRS-LAAS ? France -------------- next part -------------- An HTML attachment was scrubbed... URL: From pubconference at gmail.com Fri Dec 10 19:16:45 2021 From: pubconference at gmail.com (Pub Conference) Date: Fri, 10 Dec 2021 19:16:45 -0500 Subject: Connectionists: [Journals] Call for IEEE TNNLS Special Issue on "Stream Learning, " Submission Deadline: December 15, 2021 Message-ID: Guest Editors: Jie Lu, University of Technology Sydney, Australia; Joao Gama, University of Porto, Portugal; Xin Yao, Southern University of Science and Technology, China; Leandro Minku, University of Birmingham, UK. *Submission Deadline: December 15, 2021 [EXTENDED].* *Website: * *https://cis.ieee.org/images/files/Publications/TNNLS/special-issues/One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf* -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf Type: application/pdf Size: 109969 bytes Desc: not available URL: From david at irdta.eu Sun Dec 12 03:41:21 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 12 Dec 2021 09:41:21 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Summer: early registration January 17 Message-ID: <801877912.1308152.1639298481481@webmail.strato.com> ****************************************************************** 6th INTERNATIONAL GRAN CANARIA SCHOOL ON DEEP LEARNING DeepLearn 2022 Summer Las Palmas de Gran Canaria, Spain July 25-29, 2022 https://irdta.eu/deeplearn/2022su/ ***************** Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Early registration: January 17, 2022 ****************************************************************** SCOPE: DeepLearn 2022 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Bournemouth, and Guimar?es. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Instituci?n Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/index.php?option=com_k2&view=item&layout=item&id=360&Itemid=896 STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Wahid Bhimji (Lawrence Berkeley National Laboratory), Deep Learning on Supercomputers for Fundamental Science Joachim M. Buhmann (Swiss Federal Institute of Technology Zurich), Machine Learning & AI -- Paradigm Shift of Human Thought?! Kate Saenko (Boston University), Overcoming Dataset Bias in Deep Learning PROFESSORS AND COURSES: T?lay Adal? (University of Maryland Baltimore County), [intermediate] Data Fusion Using Matrix and Tensor Factorizations Pierre Baldi (University of California Irvine), [intermediate/advanced] Deep Learning: From Theory to Applications in the Natural Sciences Arindam Banerjee (University of Illinois Urbana-Champaign), [intermediate/advanced] Deep Generative and Dynamical Models Mikhail Belkin (University of California San Diego), [intermediate/advanced] Modern Machine Learning and Deep Learning through the Prism of Interpolation Dumitru Erhan (Google), [intermediate/advanced] Visual Self-supervised Learning and World Models Arthur Gretton (University College London), [intermediate/advanced] Probability Divergences and Generative Models Phillip Isola (Massachusetts Institute of Technology), [intermediate] Deep Generative Models Mohit Iyyer (University of Massachusetts Amherst), [intermediate/advanced] Natural Language Generation Irwin King (Chinese University of Hong Kong), [intermediate/advanced] Deep Learning on Graphs Vincent Lepetit (Paris Institute of Technology), [intermediate] Deep Learning and 3D Reasoning for 3D Scene Understanding Yan Liu (University of Southern California), [introductory/intermediate] Deep Learning for Time Series Dimitris N. Metaxas (Rutgers, The State University of New Jersey), [intermediate/advanced] Model-based, Explainable, Semisupervised and Unsupervised Machine Learning for Dynamic Analytics in Computer Vision and Medical Image Analysis Sean Meyn (University of Florida), [introductory/intermediate] Reinforcement Learning: Fundamentals, and Roadmaps for Successful Design Louis-Philippe Morency (Carnegie Mellon University), [intermediate/advanced] Multimodal Machine Learning Wojciech Samek (Fraunhofer Heinrich Hertz Institute), [introductory/intermediate] Explainable AI: Concepts, Methods and Applications Clara I. S?nchez (University of Amsterdam), [introductory/intermediate] Mechanisms for Trustworthy AI in Medical Image Analysis and Healthcare Bj?rn W. Schuller (Imperial College London), [introductory/intermediate] Deep Multimedia Processing Jonathon Shlens (Google), [introductory/intermediate] Introduction to Deep Learning in Computer Vision Johan Suykens (KU Leuven), [introductory/intermediate] Deep Learning, Neural Networks and Kernel Machines Csaba Szepesv?ri (University of Alberta), [intermediate/advanced] Tools and Techniques of Reinforcement Learning to Overcome Bellman's Curse of Dimensionality 1. Murat Tekalp (Ko? University), [intermediate/advanced] Deep Learning for Image/Video Restoration and Compression Alexandre Tkatchenko (University of Luxembourg), [introductory/intermediate] Machine Learning for Physics and Chemistry Li Xiong (Emory University), [introductory/intermediate] Differential Privacy and Certified Robustness for Deep Learning Ming Yuan (Columbia University), [intermediate/advanced] Low Rank Tensor Methods in High Dimensional Data Analysis OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by July 17, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 17, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 17, 2022. ORGANIZING COMMITTEE: Marisol Izquierdo (Las Palmas de Gran Canaria, local chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn/2022su/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://irdta.eu/deeplearn/2022su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria Universitat Rovira i Virgili Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sun Dec 12 03:39:28 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 12 Dec 2021 09:39:28 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Spring: early registration December 15 Message-ID: <1844794484.1308036.1639298368777@webmail.strato.com> ****************************************************************** 5th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2022 Spring Guimar?es, Portugal April 18-22, 2022 https://irdta.eu/deeplearn/2022sp/ ***************** Co-organized by: Algoritmi Center University of Minho, Guimar?es Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Early registration: December 15, 2021 ****************************************************************** SCOPE: DeepLearn 2022 Spring will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, and Bournemouth. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Spring is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Spring will take place in Guimar?es, in the north of Portugal, listed as UNESCO World Heritage Site and often referred to as the birthplace of the country. The venue will be: Hotel de Guimar?es Eduardo Manuel de Almeida 202 4810-440 Guimar?es http://www.hotel-guimaraes.com/ STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full in vivo online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Kate Smith-Miles (University of Melbourne), Stress-testing Algorithms via Instance Space Analysis Mihai Surdeanu (University of Arizona), Explainable Deep Learning for Natural Language Processing Zhongming Zhao (University of Texas, Houston), Deep Learning Approaches for Predicting Virus-Host Interactions and Drug Response PROFESSORS AND COURSES: Eneko Agirre (University of the Basque Country), [introductory/intermediate] Natural Language Processing in the Pretrained Language Model Era Mohammed Bennamoun (University of Western Australia), [intermediate/advanced] Deep Learning for 3D Vision Altan ?ak?r (Istanbul Technical University), [introductory] Introduction to Deep Learning with Apache Spark Rylan Conway (Amazon), [introductory/intermediate] Deep Learning for Digital Assistants Jifeng Dai (SenseTime Research), [intermediate] AutoML for Generic Computer Vision Tasks Jianfeng Gao (Microsoft Research), [introductory/intermediate] An Introduction to Conversational Information Retrieval Daniel George (JPMorgan Chase), [introductory] An Introductory Course on Machine Learning and Deep Learning with Mathematica/Wolfram Language Bohyung Han (Seoul National University), [introductory/intermediate] Robust Deep Learning Lina J. Karam (Lebanese American University), [introductory/intermediate] Deep Learning for Quality Robust Visual Recognition Xiaoming Liu (Michigan State University), [intermediate] Deep Learning for Trustworthy Biometrics Jennifer Ngadiuba (Fermi National Accelerator Laboratory), [intermediate] Ultra Low-latency and Low-area Machine Learning Inference at the Edge Lucila Ohno-Machado (University of California, San Diego), [introductory] Use of Predictive Models in Medicine and Biomedical Research Bhiksha Raj (Carnegie Mellon University), [introductory] Quantum Computing and Neural Networks Bart ter Haar Romenij (Eindhoven University of Technology), [intermediate] Deep Learning and Perceptual Grouping Kaushik Roy (Purdue University), [intermediate] Re-engineering Computing with Neuro-inspired Learning: Algorithms, Architecture, and Devices Walid Saad (Virginia Polytechnic Institute and State University), [intermediate/advanced] Machine Learning for Wireless Communications: Challenges and Opportunities Yvan Saeys (Ghent University), [introductory/intermediate] Interpreting Machine Learning Models Martin Schultz (J?lich Research Centre), [intermediate] Deep Learning for Air Quality, Weather and Climate Richa Singh (Indian Institute of Technology, Jodhpur), [introductory/intermediate] Trusted AI Sofia Vallecorsa (European Organization for Nuclear Research), [introductory/intermediate] Deep Generative Models for Science: Example Applications in Experimental Physics Michalis Vazirgiannis (?cole Polytechnique), [intermediate/advanced] Machine Learning with Graphs and Applications Guowei Wei (Michigan State University), [introductory/advanced] Integrating AI and Advanced Mathematics with Experimental Data for Forecasting Emerging SARS-CoV-2 Variants Xiaowei Xu (University of Arkansas, Little Rock), [intermediate/advanced] Deep Learning for NLP and Causal Inference Guoying Zhao (University of Oulu), [introductory/intermediate] Vision-based Emotion AI OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by April 10, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by April 10, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by April 10, 2022. ORGANIZING COMMITTEE: Dalila Dur?es (Braga, co-chair) Jos? Machado (Braga, co-chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) Paulo Novais (Braga, co-chair) David Silva (London, co-chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn/2022sp/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will get exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Accommodation suggestions are available at https://irdta.eu/deeplearn/2022sp/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Centro Algoritmi, University of Minho, Guimar?es School of Engineering, University of Minho Intelligent Systems Associate Laboratory, University of Minho Rovira i Virgili University Municipality of Guimar?es Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From caspar.schwiedrzik at googlemail.com Sun Dec 12 06:02:04 2021 From: caspar.schwiedrzik at googlemail.com (Caspar M. Schwiedrzik) Date: Sun, 12 Dec 2021 12:02:04 +0100 Subject: Connectionists: =?utf-8?q?PhD_student_position_in_the_NCC_lab_at_?= =?utf-8?q?the_European_Neuroscience_Institute_G=C3=B6ttingen=2C_Ge?= =?utf-8?q?rmany?= Message-ID: The NCC Lab at ENI G?ttingen is looking for an outstanding *PhD student (f/m/d)* Specialization: interested in studying face perception and predictive processing in non-human primates Limitation: Appointment until 31.12.2025 Working period: 65 % (25,025h/week) Tariff: Entgelt nach TV-L Announcement published on 10.12.2021 Vacancy from 12.08.2021 Application deadline: 14.01.2022 At the University of G?ttingen, a new Collaborative Research Center (CRC) 1528 ?Cognition of Interaction? will be established with funding from the German Research Foundation (DFG). In 22 projects, the CRC 1528 ?Cognition of Interaction? investigates how fundamental cognitive functions and their neurobiological foundations contribute to human and nonhuman primate social behavior and social interactions. The CRC is formed by a highly interdisciplinary consortium formed by systems and computational neuroscientists, data scientists, psychologists and behavioral and cognitive biologists. Partner institutions are the University of G?ttingen, the University Medical Center, the German Primate Center, the Max Planck Institute for Dynamics and Self-Organization, the University Hospital Hamburg-Eppendorf and the Weizmann Institute of Science. In the context of this CRC, the Neural Circuits and Cognition Lab of Caspar Schwiedrzik at the European Neuroscience Institute G?ttingen is looking for an outstanding PhD student interested in studying face perception and predictive processing. The project investigates neural mechanisms of face perception and predictive processing at the level of circuits and single cells, utilizing functional magnetic resonance imaging (fMRI) in combination with electrophysiology and pharmacology in non-human primates. The Neural Circuits and Cognition Lab seeks to understand the cortical basis and computational principles of visual perception and experience-dependent plasticity in the macaque and human brain. To this end, we use a multimodal approach including fMRI-guided electrophysiological recordings in non-human primates and fMRI and iEEG in humans. The PhD student will play a key role in our research efforts in this area. The lab is located at the European Neuroscience Institute G?ttingen (https://www.eni-g.de) and the German Primate Center ( https://www.dpz.eu), which are interdisciplinary research centers with international faculty and students pursuing cutting-edge research in neuroscience. Further scientific exchange within the CRC and the Leibniz ScienceCampus ?Primate Cognition? (https://www.primate-cognition.eu) ensures a broad interdisciplinary framework for networking and cooperation. The PhD student will have access to a dedicated imaging center with a dedicated 3T research scanner, state-of-the-art electrophysiology, and behavioral setups. For an overview of our work and representative publications, please see our website https://www.eni-g.de/groups/neural-circuits-and-cognition. The position is funded until 31.12.2025. The successful candidate will join one of the many excellent graduate schools on the G?ttingen Campus.Candidates should have a degree (master, diploma or equivalent) in a relevant field (e.g., neuroscience, psychology, biology), and ideally prior experience with non-human primates, strong quantitative, programming, and experimental skills, and share a passion for understanding the neural basis of visual perception and its plasticity. A good command of English is a requirement, but fluency in German is not essential. Interested candidates should send their curriculum vitae, a description of their scientific interests and the names and contact information of two references who are able to comment on your academic background and who agreed to be contacted to Caspar M. Schwiedrzik (cschwie3 at gwdg.de). The University Medical Center G?ttingen is committed to professional equality. We therefore seek to increase the proportion of under-represented genders. Applicants with disabilities and equal qualifications will be given preferential treatment. We look forward to receiving your application by 14.01.2022: University Medical Center G?ttingen European Neuroscience Institute G?ttingen Dr. Caspar Schwiedrzik Group Leader Grisebachstr. 5 37077 G?ttingen Tel.: +49 0551/39-61371 E-Mail: cschwie3 at gwdg.de Web: http://www.eni-g.de/ Contact person: For questions about the position or project, please contact Caspar M. Schwiedrzik (cschwie3 at gwdg.de). For questions about the application procedure, please contact Christiane Becker (c.becker at eni-g.de). Please send your application via e-mail in PDF-format or via mail in copy and not in folders. -------------- next part -------------- An HTML attachment was scrubbed... URL: From chunzhiyi at hit.edu.cn Sun Dec 12 20:14:29 2021 From: chunzhiyi at hit.edu.cn (=?UTF-8?B?6KGj5rez5qSN?=) Date: Mon, 13 Dec 2021 09:14:29 +0800 (GMT+08:00) Subject: Connectionists: =?utf-8?q?=5Bjournals=5DCFP=3A_=22Sensing=2C_Esti?= =?utf-8?q?mating=2C_and_Analyzing_Human_Movements_for_Human=E2=80=93Robot?= =?utf-8?q?_Interaction=22?= Message-ID: <6d5c8440.3b0c.17db15af9ac.Coremail.chunzhiyi@hit.edu.cn> Dear Colleagues, We would like to announce a new SI for"Sensing, Estimating, and Analyzing Human Movements for Human?Robot Interaction" in sensors. Recent advances in human?robot interaction (HRI) are playing an increasingly pivotal role in a wide spectrum of robots, ranging from household to industrial, and from virtual interaction to closely physical collaboration. Due to the core function in HRI systems, numerous efforts and intensive attentions are paid to sensing, estimating, and analyzing the continuous and high-dimensional human movements so as to semantically decode and reflect motor intent and even latent beliefs of human motor control. The purpose of this Special Issue is therefore to describe the state of the art in human neuromuscular and cognitive behaviors reflected by human movements and to present the challenges associated with leveraging such knowledge in human-centered design and control of HRI systems. This Special Issue aims to present the latest results and emerging algorithmic techniques of sensing, estimating, and analyzing human movements in human?robot interaction. This fits the scope of Sensors as algorithms are used to process the information collected by sensors and sensor networks. Prof. Dr. Feng Jiang Prof. Dr. Jie Liu Dr. Chunzhi Yi Guest Editors Key words: Human?robot interaction Human movement analysis Human augmentation Inner belief estimation Neuromuscular control Human intent perception Bio-inspired design and control of robots You can find the website of the SI at https://www.mdpi.com/journal/sensors/special_issues/Sensing_Estimating_Analyzing_HRI Best, YI Chunzhi -------------- next part -------------- An HTML attachment was scrubbed... URL: From poirazi at imbb.forth.gr Mon Dec 13 02:54:00 2021 From: poirazi at imbb.forth.gr (Yiota Poirazi) Date: Mon, 13 Dec 2021 09:54:00 +0200 Subject: Connectionists: DENDRITES 2022 call for abstracts Message-ID: DENDRITES 2022 EMBO Workshop on Dendritic Anatomy, Molecules and Function Heraklion, Crete, Greece 23-26 May 2022 http://meetings.embo.org/event/20-dendrites Dear Colleagues, We are pleased to announce the solicitation of abstracts for short oral or poster presentations at the EMBO Workshop on DENDRITES 2022, which will take place in Heraklion, Crete on 23-26 May 2022. This is the 4th of a very successful series of meetings on the island of Crete that is dedicated to dendrites. The meeting will bring together scientific leaders from around the globe to present their theoretical and experimental work on dendrites. The meeting program is designed to facilitate discussions of new ideas and discoveries, in a relaxed atmosphere that emphasizes interaction. Please register (no payment required) and submit your abstract online at: http://meetings.embo.org/event/20-dendrites Submissions of abstracts are due by *February 1st, **2022* Notifications will be provided by February 28th, 2022 Registration payment due by April 15th, 2022 Potential attendees are strongly encouraged to submit an abstract as presenters will have registration priority. For more information about the conference, please refer to our web site or send email to info at mitos.com.gr We look forward to seeing you in person at DENDRITES 2022! The organizers, Yiota Poirazi, Kristen Harris, Matthew Larkum, Michael H?usser -- Panayiota Poirazi, Ph.D. Research Director Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810-391139 /-391238 Fax: +30 2810-391101 ?mail: poirazi at imbb.forth.gr Lab site: www.dendrites.gr -------------- next part -------------- An HTML attachment was scrubbed... URL: From O.Inel at tudelft.nl Mon Dec 13 04:02:13 2021 From: O.Inel at tudelft.nl (Oana Inel) Date: Mon, 13 Dec 2021 09:02:13 +0000 Subject: Connectionists: Call-for-Papers Special Issue "Explainable User Models" (Multimodal Technologies and Interaction Journal) Message-ID: <8F545863-739A-4419-A70C-B5E5B7DD4329@tudelft.nl> ? Apologies for cross-posting ? Special Issue "Explainable User Models" A special issue of Multimodal Technologies and Interaction (ISSN 2414-4088). Important Dates & Facts: Manuscripts due by: February 20, 2022 Notification to authors: March 15, 2022 Website: https://www.mdpi.com/journal/mti/special_issues/Explainable_User_Models Benefits of submission: - Experienced Guest Editor - Open Access with quick processing time - High Visibility: Indexed within Scopus, ESCI (Web of Science), Inspec, and many other databases. - Journal Rank: CiteScore - Q2 (Computer Science Applications) Special Issue Information This special issue addresses research on Explainable User Models. As AI systems? actions and decisions will significantly affect their users, it is important to be able to understand how an AI system represents its users. It is a well-known hurdle that many AI algorithms behave largely as black boxes. One key aim of explainability is, therefore, to make the inner workings of AI systems more accessible and transparent. Such explanations can be helpful in the case when the system uses information about the user to develop a working representation of the user, and then uses this representation to adjust or inform system behavior. E.g., an educational system could detect whether students have a more internal or external locus of control, a music recommender system could adapt the music it is playing to the current mood of a user, or an aviation system could detect the visual memory capacity of its pilots. However, when adapting to such user models it is crucial that these models are accurately detected. Furthermore, for such explanations to be useful, they need to be able to explain or justify their representations of users in a human-understandable way. This creates a necessity for techniques that will create models for the automatic generation of satisfactory explanations intelligible for human users interacting with the system. The scope of the special issue includes but is not limited to: Detection and Modelling ? Novel ways of Modeling User Preferences ? Types of information to model (Knowledge, Personality, Cognitive differences, etc.) ? Distinguishing between stationary versus transient user models (e.g., Personality vs Mood) ? Context modeling (e.g., at work versus at home, lean in versus lean out activities) ? User models from heterogeneous sources (e.g., behavior, ratings, and reviews) ? Enrichment and Crowdsourcing for Explainable User Models Ethics ? Detection of sensitive or rarely reported attributes (e.g., gender, race, sexial orientation) ? Implicit user modeling versus explicit user modeling (e.g., questionnaires versus inference from behavior) ? User modeling for self actualization (e.g., user modeling to improve dietary or news consumption habits) Human understandability ? Metrics and methodologies for evaluating fitness for the purpose of explanations ? Balancing completeness and understandability for complex user models ? Explanations to mitigate human biases (e.g., confirmation bias, anchoring) ? Effect of user model explanation on subsequent user interaction (e.g., simulations, and novel evaluation methodologies) Effectiveness ? Analysis or comparison of context of use of explanation (e.g., risk, time pressure, error tolerance) ? Analysis of context of use of system (e.g., decision support, prediction) ? Analysis or comparison of effect of explaining in specific domains (e.g., education, health, recruitment, security) Adaptive presentation of the explanations ? For different types of user ? Interactive explanations ? Investigation of which presentational aspects are beneficial to tailor in the explanation (e.g., level of detail, terminology, modality text or graphics, level of interaction) Prof. Dr. Nava Tintarev Ms. Oana Inel Guest Editors -------------- next part -------------- An HTML attachment was scrubbed... URL: From mpavone at dmi.unict.it Mon Dec 13 15:28:26 2021 From: mpavone at dmi.unict.it (Mario Pavone) Date: Mon, 13 Dec 2021 21:28:26 +0100 Subject: Connectionists: MIC 2022 - 14th Metaheuristics International Conference, Ortigia-Syracuse, Italy Message-ID: <20211213212826.Horde.4hyoVeph4B9ht6zqb8TgxLA@mbox.dmi.unict.it> Apologies for cross-posting. Appreciate if you can distribute this CFP to your network. ********************************************************* MIC 2022 - 14th Metaheuristics International Conference 11-14 July 2022, Ortigia-Syracuse, Italy https://www.ANTs-lab.it/mic2022/ mic2022 at ANTs-lab.it ********************************************************* ** Submission deadline: 30th March 2022 ** NEWS ** New Plenary Speaker: Kalyanmoy Deb, Michigan State University ** Proceedings will be published in LNCS Volume, Springer ** Special Issue in ITOR journal *Scope of the Conference ======================== The Metaheuristics International Conference (MIC) conference series was established in 1995 and this is its 14th edition! MIC is nowadays the main event focusing on the progress of the area of Metaheuristics and their applications. As in all previous editions, provides an opportunity to the international research community in Metaheuristics to discuss recent research results, to develop new ideas and collaborations, and to meet old and make new friends in a friendly and relaxed atmosphere. Considering the particular moment, the conference will be held in presence and online mode. Of course, in case the conference will be held in presence, the organizing committee will ensure compliance of all safety conditions. MIC 2022 is focus on presentations that cover different aspects of metaheuristic research such as new algorithmic developments, high-impact and original applications, new research challenges, theoretical developments, implementation issues, and in-depth experimental studies. MIC 2022 strives a high-quality program that will be completed by a number of invited talks, tutorials, workshops and special sessions. *Plenary Speakers ======================== + Christian Blum, Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC) + Kalyanmoy Deb, Michigan State University, USA + Salvatore Greco, University of Catania, Italy + Holger H. Hoos, Leiden University, The Netherlands + El-Ghazali Talbi, University of Lille, France Important Dates ================ Submission deadline March 30th, 2022 Notification of acceptance May 10th, 2022 Camera ready copy May 25th, 2022 Early registration May 25th , 2022 Submission Details =================== MIC 2022 accepts submissions in three different formats: ??S1) Regular paper: novel and original research contributions of a maximum of 15 pages (LNCS format) ??S2) Short paper: extended abstract of novel research works of 6 pages (LNCS format) ??S3) Oral/Poster presentation: high-quality manuscripts that have recently, within the last year, been submitted or accepted for journal publication. All papers must be prepared using Lecture Notes in Computer Science (LNCS) template, and must be submitted in PDF at the link: https://www.easychair.org/conferences/?conf=mic2022 Proceedings and special issue ============================ Accepted papers in categories S1 and S2 will be published as post-proceedings in Lecture Notes in Computer Science series by Springer. Accepted contributions of category S3 will be considered for oral or poster presentations at the conference based on the number received and the slots available, and will not be included into the LNCS proceedings. An electronic book instead will be prepared by the MIC 2022 organizing committee, and made available on the website. In addition, a post-conference special issue in International Transactions in Operational Research (ITOR) will be considered for the significantly extended and revised versions of selected accepted papers from categories S1 and S2. Conference Location ==================== MIC 2022 will be held in the beautiful Ortigia island, the historical centre of the city of Syracuse, Sicily-Italy. Syracuse is very famous for its ancient ruins, with particular reference to the Roman Amphitheater, Greek Theatre, and the Orecchio di Dionisio (Ear of Dionisio) that is a limestone cave shaped like a human ear. Syracuse is also the city where the greatest mathematician Archimede was born. https://www.siracusaturismo.net/multimedia_lista.asp MIC'2022 Conference Chairs ============================== Conference Chairs - Luca Di Gaspero, University of Undine, Italy - Paola Festa, University of Naples, Italy - Amir Nakib, Universit? Paris Est Cr?teil, France - Mario Pavone, University of Catania, Italy -- Mario F. Pavone, PhD Associate Professor Dept of Mathematics and Computer Science University of Catania V.le A. Doria 6 - 95125 Catania, Italy --------------------------------------------- tel: +39 095 7383034 mobile: +39 3384342147 Email: mpavone at dmi.unict.it http://www.dmi.unict.it/mpavone/ FB: https://www.facebook.com/mfpavone Skype: mpavone ========================================================= MIC 2022 - 14th International Metaheuristics Conference 11-14 July 2022, Ortigia-Syracuse, Italy https://www.ants-lab.it/mic2022/ ========================================================= From franciscocruzhh at gmail.com Mon Dec 13 15:16:25 2021 From: franciscocruzhh at gmail.com (Francisco Cruz) Date: Mon, 13 Dec 2021 17:16:25 -0300 Subject: Connectionists: Deadline Extension -- Special Issue on Human-aligned Reinforcement Learning for Autonomous Agents and Robots @NCAA journal Message-ID: UPDATE: the deadline for submission has been extended until 28th February 2022. However, the review process for manuscripts will start as soon as they are being received. If you have further questions, please do not hesitate to contact the guest editors. See relevant details at: https://www.springer.com/journal/521/updates/19055662 ** Call for papers ** Topical Collection on Human-aligned Reinforcement Learning for Autonomous Agents and Robots at the Springer journal Neural Computing and Applications. ** Topics ** The main topics of interest in the call for submissions are explainability, interactivity, safety, and ethics in social robotics and autonomous agents, especially from a reinforcement learning perspective. In this regard, approaches with special interest for this topical collection are (but not limited to): - Explainability, interpretability, and transparency methods for feature-oriented and goal-driven RL. - Explainable robotic systems with RL approaches. - Assisted and interactive RL in human-robot and human-agent scenarios. - Human-in-the-loop RL and applications. - RL from demonstrations and imperfect demonstrations. - Robot and agent learning from multiple human sources. - Multi-robot systems with human collaboration. - Safe exploration during learning. - Ethical reasoning and moral uncertainty. - Fairness in RL and multi-agent systems. - Theory of mind based RL frameworks. - Use of human priors in RL. ** Provisional deadlines ** - Deadline for submissions: December 15, 2021 (extended to 28th February, 2022) - Deadline for review: February 15, 2022 - Decisions: March 15, 2022 - Revised manuscript submission: May 15, 2022 - Deadline for second review: June 15, 2022 - Final decisions: June 30, 2022 ** Guest editors ** Dr. Francisco Cruz (Lead guest editor) School of Information Technology Deakin University, Australia Dr. Thommen George Karimpanal Applied Arti?cial Intelligence Institute (A2I2) Deakin University, Australia Dr. Miguel Solis, Facultad de Ingenieria Universidad Andres Bello, Chile Dr. Pablo Barros Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology (IIT), Italy A/Prof. Richard Dazeley School of Information Technology Deakin University, Australia ** More details at: ** https://www.springer.com/journal/521/updates/19055662 -------------- next part -------------- An HTML attachment was scrubbed... URL: From lapishc at gmail.com Mon Dec 13 17:29:12 2021 From: lapishc at gmail.com (Christopher C. Lapish) Date: Mon, 13 Dec 2021 17:29:12 -0500 Subject: Connectionists: Postdoctoral Fellowship Opening Message-ID: *Postdoctoral Fellowship in Computational Neuroscience* A position is available immediately in the Lapish Laboratory at the rank of postdoctoral fellow. This position will study how the computations that underlie decision-making are impaired by stress and addiction. A PhD is required in an applicable discipline (Neuroscience, Physics, Statistics, etc.). This is an NIH grant-funded position. An individual with experience in statistical analysis of neural data, computational neuroscience, or a related discipline is sought. This individual will be required to analyze existing neural data and build novel simulations of how decision-making is impaired in the addicted brain. This individual will work closely with the Lapish lab, and their collaborators toward this goal. This listing will remain open until the position is filled and applications will be evaluated on a rolling basis. If interested in applying, please email the following information to Dr. Christopher Lapish (clapish at iu.edu): Curriculum Vita (CV) including publications and skills Contact information of 3 references. *IUPUI is committed to being a welcoming campus community that reflects and enacts the values of diversity, equity and inclusion that inform academic excellence. We seek candidates who will not only enhance our representational diversity but whose research, teaching, and community engagement efforts contribute to diverse, equitable, and inclusive learning and working environments for our students, staff, and faculty. IUPUI condemns racism in all its forms and has taken an anti-racist stance that moves beyond mere statements to interrogating its policies, procedures, and practices. We hope to identify individuals who will assist in our mission to dismantle racism so that everyone has the opportunity to succeed at IUPUI.* https://jobs.sciencecareers.org/job/574566/computational-neuroscience-focused-postdoctoral-position/ -- Christopher C. Lapish PhD Associate Professor Indiana University Purdue University Indianapolis Department of Psychology LD 124, 402 N. Blackford St. Indianapolis, IN 46202-3275 317-274-6931 (Office) www.lapishlab.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From juyang.weng at gmail.com Mon Dec 13 18:52:26 2021 From: juyang.weng at gmail.com (Juyang Weng) Date: Mon, 13 Dec 2021 18:52:26 -0500 Subject: Connectionists: Protocol Flaws of Error-Backprop Based Neural Networks such as CNNs and LSTMs Message-ID: Dear Colleagues: Please feel free to respond to the following allegations. Post Selections in AI Papers in Science since 2015 and the Appropriate Protocol http://www.cse.msu.edu/~weng/research/2021-12-13-Science-AI-Papers-Post-Seleciton-Protocol.pdf A Report to Nature about Technical Flaws of Post-Selections Using Test Sets (PSUTS) http://www.cse.msu.edu/~weng/research/2021-06-28-Report-to-Nature-specific-PSUTS.pdf -- Juyang (John) Weng -------------- next part -------------- An HTML attachment was scrubbed... URL: From pubconference at gmail.com Mon Dec 13 18:59:43 2021 From: pubconference at gmail.com (Pub Conference) Date: Mon, 13 Dec 2021 18:59:43 -0500 Subject: Connectionists: [Journals] Call for IEEE TNNLS Special Issue on "Stream Learning, " Submission Deadline: December 15, 2021 Message-ID: Guest Editors: Jie Lu, University of Technology Sydney, Australia; Joao Gama, University of Porto, Portugal; Xin Yao, Southern University of Science and Technology, China; Leandro Minku, University of Birmingham, UK. *Submission Deadline: December 15, 2021 [EXTENDED].* *Website: * *https://cis.ieee.org/images/files/Publications/TNNLS/special-issues/One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf* -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: One-Page_IEEE_Transactions_on_NNLS-SI-CFP-Update.pdf Type: application/pdf Size: 109969 bytes Desc: not available URL: From dengdehao at gmail.com Tue Dec 14 01:27:43 2021 From: dengdehao at gmail.com (Teng Teck Hou) Date: Tue, 14 Dec 2021 14:27:43 +0800 Subject: Connectionists: [IEEE SSCI 2022] Call for Symposiums/Special Sessions/Tutorials Message-ID: <004701d7f0b3$b55ef370$201cda50$@gmail.com> [Apologies for cross-postings] #################################################################### IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022) December 4 - December 7, 2022 | Singapore http://ieeessci2022.org ****Call for Symposiums/Special Sessions**** ****Call for Tutorials**** #################################################################### **************** ****Synopsis**** **************** IEEE SSCI is an established flagship annual international series of symposia on computational intelligence sponsored bythe IEEE Computational Intelligence Society to promote and stimulate discussion on the latest theory, algorithms,applications and emerging topics on computational intelligence. By co-locating multiple symposia under one roof, eachdedicated to a specific topic in the CI domain, IEEE SSCI aims to encourage cross-fertilization of ideas and provide aunique platform for top researchers, professionals, and students from all around the world to discuss and present theirfindings. IEEE SSCI 2022 will feature keynote addresses, tutorials, panel discussions and special sessions, all of whichare open to all participants. The conference proceedings of the IEEE SSCI will be included in the IEEE Xplore andindexed by all major databases. List of Confirmed Symposia and Special Sessions * Adaptive Dynamic Programming and Reinforcement Learning(IEEE ADPRL) * Advancing Capabilities of Simulation Models withComputational Intelligence (ASM) * Artificial Life (IEEE ALIFE) * Artificial Intelligence-based Uncertainty Quantification(AUQ) * CI and Ensemble Learning (IEEE CIEL) * CI for Astroinformatics (IEEE CIAstro) * CI for Engineering Solutions (IEEE CIES) * CI for Human-like Intelligence (IEEE CIHLI) * CI for Multimedia Signal and Vision Processing (IEEE CIMSIVP) * CI for Security and Defense Applications (IEEE CISDA) * CI in Agriculture (IEEE CIAg) * CI in Biometrics and Identity Management (IEEE CIBIM) * CI for Brain Computer Interfaces (IEEE CIBCI) * CI in Control and Automation (IEEE CICA) * CI in Cyber Security (IEEE CICS) * CI in Data Mining (IEEE CIDM) * CI in Feature Analysis, Selection and Learning in Imageand Pattern Recognition (IEEE FASLIP) * CI in Healthcare and E-health (IEEE CICARE) * CI in IoT and Smart Cities (IEEE CIIoT) * CI in Remote Sensing (IEEE CIRS) * CI in Soil and Water Management (SWM) * CI in Vehicles and Transportation Systems (IEEE CIVTS) * Computational Intelligence in Big Data (IEEE CIBD) * Cooperative Metaheuristics (IEEE SCM) * Deep Learning (IEEE DL) * Differential Evolution (IEEE SDE) * Evolving and Autonomous Learning Systems (IEEE EALS) * Evolving Deep and Transfer Learning Models forComputer Vision and Medical Imaging (ECV) * Evolutionary Neural Architecture Search and Applications(IEEE ENASA) * Evolutionary Scheduling and CombinatorialOptimisation (IEEE ESCO) * Explainable Data Analytics in Computational Intelligence (IEEE EDACI) * Ethical, Social and Legal Implications of ArtificialIntelligence (IEEE ETHAI) * Foundations of CI (IEEE FOCI) * Games (GAMES) * Human and Machine Intelligence in CollaborativeDecision Making (HMI) * Immune Computation (IEEE IComputation) * Intelligent Agents (IEEE IA) * Model-Based Evolutionary Algorithms (IEEE MBEA) * Multicriteria Decision-Making (IEEE MCDM) * Nature-Inspired Computation in Engineering (IEEENICE) * Robotic Intelligence in Informationally StructuredSpace (IEEE RiiSS) * Swarm Intelligence Symposium (IEEE SIS) ******************************************** ****Call for Symposiums/Special Sessions**** ******************************************** IEEE SSCI 2022 welcomes your proposals for new symposia and special sessions. Inquiries and submission of proposals should be addressed to the Program Chairs. https://www.ieeessci2022.org/call_for_special_sessions.html ************************** ****Call for Tutorials**** ************************** IEEE SSCI 2022 solicits proposals for tutorials on specific topics of interests, which will form an integral part of the conference program. Inquiries and submission of tutorial proposals should be addressed to the Keynote/Tutorial Chairs. https://www.ieeessci2022.org/call_for_tutorials.html *********************** ****Important Dates**** *********************** * Symposia/Session/Tutorial Proposals Friday, 1st April 2022 * Paper Submission Deadline Friday, 1st July 2022 * Notification to Authors Thursday, 1st September 2022 * Full Manuscript Submission Monday. 19th September 2022 * Early Bird Registration Monday, 26th September 2022 * IEEE SSCI 2022 Conference 4th December to 7th December 2022 **************************** ****Organizing Committee**** **************************** * Advisory Chairs Kay-Chen TAN City University of Hong Kong Yew-Soon ONG Nanyang Technological University * General Chairs Ah-Hwee TAN Singapore Management University Dipti SRINIVASAN National University of Singapore Chunyan MIAO Nanyang Technological University * Program Chairs Hisao ISHIBUCHI Southern University of Science andTechnology Chee-Keong KWOH Nanyang Technological University * Finance Chair Jian-Chao YAO DSO National Laboratories * Keynote / Tutorial Chairs Yaochu JIN Bielefeld University Mahardhika PRATAMA Nanyang Technological University * Exhibit / Competition Chair Chi-Keong GOH AI2Labs * Publication Chairs Anupam TRIVEDI National University of Singapore Keeley CROCKETT Manchester Metropolitan University * Publicity Chairs Teck-Hou TENG ST Engineering Catherine HUANG McAfee AI Research Pauline C. HADDOW Norwegian University of Science and Technology Jialin LIU Southern University of Science and Technology * Local Organizing Chairs Di WANG Nanyang Technological University Zhaoxia WANG Singapore Management University Hao ZHANG Nanyang Technological University ******************************** ****Sponsoring Organizations**** ******************************** IEEE Computational Intelligence Society IEEE Singapore Section Singapore Exhibition & Convention Bureau ******************************* ****Organizing Institutions**** ******************************* Singapore Management University National University of Singapore Nanyang Technological University -------------- next part -------------- An HTML attachment was scrubbed... URL: From cgf at isep.ipp.pt Tue Dec 14 17:08:15 2021 From: cgf at isep.ipp.pt (Carlos) Date: Tue, 14 Dec 2021 22:08:15 +0000 Subject: Connectionists: CFP: HLPP 2022: International Symposium on International Symposium on High-Level Parallel Programming and Applications Message-ID: <2e353097-749b-0e38-11ce-2621c92cf96b@isep.ipp.pt> --------------- CALL FOR PAPERS --------------- HLPP 2022 The 15th International Symposium on High-level Parallel Programming and Applications Porto, Portugal, 7-8 July, 2022 https://hlpp2022.dcc.fc.up.pt/ ---------------------- Aims and scope of HLPP ---------------------- As processor and system manufacturers increase the amount of both inter- and intra-chip parallelism it becomes crucial to provide the software industry with high-level, clean and efficient tools for parallel programming. Parallel and distributed programming methodologies are currently dominated by low-level techniques such as send/receive message passing, or equivalently unstructured shared memory mechanisms. Higher-level, structured approaches offer many possible advantages and have a key role to play in the scalable exploitation of ubiquitous parallelism. Since 2001 the HLPP series of workshops/symposia has been a forum for researchers developing state-of-the-art concepts, tools and applications for high-level parallel programming. The general emphasis is on software quality, programming productivity and high-level performance models. The 15th Symposium on High-Level Parallel Programming and Applications will be held in the Porto, Portugal. ------ Topics ------ HLPP 2022 invites papers on all topics in high-level parallel programming, its tools and applications including, but not limited to, the following aspects: * High-level programming, performance models (BSP, CGM, LogP, MPM, etc.) and tools * Declarative parallel programming methodologies * Algorithmic skeletons and constructive methods * Declarative parallel programming languages and libraries: semantics and implementation * Verification of declarative parallel and distributed programs * Software synthesis, automatic code generation for parallel programming * Model-driven software engineering with parallel programs * High-level programming models for heterogeneous/hierarchical platforms * High-level parallel methods for large structured and semi-structured datasets * Applications of parallel systems using high??-level languages and tools * Formal models of timing and real-time verification for parallel systems ------------------ Program Chairs ------------------ In?s Dutra, University of Porto, Portugal Jorge Barbosa, University of Porto, Portugal Miguel Areias, University of Porto, Portugal ------------------ Publicity Chair ------------------ Carlos Ferreira, Polytechnic Institute of Porto ----------------- Program Committee ----------------- TBA ---------------- Important dates ---------------- Submission deadline: April 1, 2022(AoE) Author notification: June 3, 2022 Camera-ready for draft proceedings: July 1, 2022 Early registration deadline: June 8, 2022 Symposium: July 7-8 (Thursday/Friday) IJPP (HLPP special issue) submission deadline: October 28, 2022 IJPP (HLPP special issue) camera-ready for journal publication: December 2, 2022 ---------------- Paper submission ---------------- Papers submitted to HLPP 2022 must describe original research results and must not have been published or simultaneously submitted anywhere else. Manuscripts must be prepared with the Springer IJSS latex macro package using the single column option (\documentclass[smallextended]{svjour3}) and submitted via the EasyChair Conference Management System as one pdf file. The strict page limit for initial submission and camera-ready version is 20 pages in the aforementioned format. Each paper will receive a minimum of three reviews by members of the international technical program committee. Papers will be selected based on their originality, relevance, technical clarity and quality of presentation. After the symposium the authors of the accepted papers will have ample time to revise their papers and to incorporate the potential comments and remarks of their colleagues. We expect the HLPP 2022 special issue of the International Journal of Parallel Programming (IJPP) to appear online-first by the end of the year and the printed edition in mid-2023. ----------- Proceedings ----------- Accepted papers will be distributed as informal draft proceedings during the symposium and will be published by Springer in a special issue of the International Journal of Parallel Programming (IJPP). ----- Venue ----- HLPP 2022 will be hosted by the Dept. of Computer Science (GPS coords 41.152545, -8.640758) of the Faculty of Sciences of the University of Porto (FCUP). Participants may reserve rooms in several of the nearby Hotels. As the symposium will be held in the tourist season, the organizers recommend a timely reservation of rooms. Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. Ant?nio Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From hausser at gmail.com Tue Dec 14 18:25:41 2021 From: hausser at gmail.com (Michael Hausser) Date: Tue, 14 Dec 2021 23:25:41 +0000 Subject: Connectionists: Optical Biology PhD Program at UCL Message-ID: We invite applications for the *Optical Biology 4-year PhD program* at UCL. This program brings together neuroscientists, cell biologists, physicists, chemists and computational scientists at UCL, with world-leading industrial and academic partners, to deliver an integrated training programme in the most advanced optical methods and analysis tools. The program offers a strong focus on bespoke personal mentorship and career development support for students. Full funding will be available for top-ranked applicants; research expenses will also be provided, as well as funds to attend international courses and meetings. We also provide transition costs at the end of the PhD to help you move to the next stage of your career. The EXTENDED application deadline is *Monday* *20 December 2021*. For more details and information about applying please visit: https://opticalbiology.org Applications and queries should be sent to: opticalbiologyPhD at ucl.ac.uk ? Michael Hausser Director, Optical Biology PhD Program Facilitator, International Brain Laboratory Professor of Neuroscience, UCL tel +44-20-7679-6756 email m.hausser at ucl.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From smart at neuralcorrelate.com Tue Dec 14 17:25:44 2021 From: smart at neuralcorrelate.com (smart at neuralcorrelate.com) Date: Tue, 14 Dec 2021 17:25:44 -0500 Subject: Connectionists: Vote for the Best Illusion of the Year! The 17th Best Illusion of the Year Contest In-Reply-To: <0b7801d7f136$c6b556e0$542004a0$@neuralcorrelate.com> References: <0b7801d7f136$c6b556e0$542004a0$@neuralcorrelate.com> Message-ID: <0c0601d7f139$899fcc60$9cdf6520$@neuralcorrelate.com> Worldwide voting for the 17th Best Illusion of the Year Contest starts at 12pm EST on Wednesday, December 15th, and will remain open until 3pm EST on Sunday, December 19th. The 1st place winner will receive $1,000, the 2nd place winner $2,000, and the 3rd place winner $1,000 USD. The Best Illusion of the Year Contest is now an annual virtual event, in which anybody with an internet connection (that means YOU!) can vote to pick the Top 3 Winners from the Top 10 Finalists. The Top 10 Finalists, selected from dozens of entries from countries all around the world, will be publicly revealed at voting time. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse ---------------------------------------------------------- Susana Martinez-Conde, PhD Author, Champions of Illusion and Sleights of Mind Professor of Ophthalmology, Neurology, and Physiology & Pharmacology Director, Laboratory of Integrative Neuroscience 2014 Society for Neuroscience's Science Educator Award 2014 Empire Innovator Scholar State University of New York (SUNY) Downstate Health Sciences University 450 Clarkson Ave, Brooklyn NY 11203, USA Email: smart at neuralcorrelate.com Phone: +1 718-270-4520 http://smc.neuralcorrelate.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From tobi at ini.uzh.ch Wed Dec 15 04:10:52 2021 From: tobi at ini.uzh.ch (Tobi Delbruck (UZH-ETH)) Date: Wed, 15 Dec 2021 10:10:52 +0100 Subject: Connectionists: 2021 Misha Mahowald Prize for Neuromorphic Engineering awards announced Message-ID: <0d2990c9-bf04-1d03-9410-35b65f91a079@ini.uzh.ch> The winners of the 2021 Misha Mahowald Prize for Neuromorphic Engineering awards were announced. The 2021 prize has been awarded to two teams of researchers who used neuromorphic principles to build devices that help disabled humans improve sensory and motor interaction with the world. Please see https://www.mahowaldprize.org/prize-awards/prize-2021 . -- Tobi Delbruck, Sensors Group: http://sensors.ini.uzh.ch Inst. for Neuroinformatics, UZH-ETH Zurich: http://www.ini.uzh.ch Building 55, Room G84, Winterthurerstr. 190, CH-8057 Zurich, Switzerland Tel lab +41 44 635 3038, Swiss cell +41 76 629 1500 (whatsapp), USA cell +1 626 510 2646, skype tobidelbruck From malin.sandstrom at incf.org Wed Dec 15 03:27:11 2021 From: malin.sandstrom at incf.org (=?UTF-8?Q?Malin_Sandstr=C3=B6m?=) Date: Wed, 15 Dec 2021 09:27:11 +0100 Subject: Connectionists: Call for INCF mentors and project ideas for GSOC 2022 - deadline January 15 & 25 Message-ID: Dear all, ---- please forward this call to potentially interested mentors in your network --- INCF will apply to be a mentor organization in Google Summer of Code for the 12th time running. We are calling for open source software development project ideas with some sort of *neuro connection* - fixes or extensions to big/broadly applicable or small/niche tools used by neuroscience researchers, efforts and initiatives in the broad field of computational neuroscience. If your project supports or implements INCF endorsed standards or best practices , we especially encourage you to apply. We are also* looking for mentors who are willing to take on student-proposed projects *that fit their interests. As you may have seen earlier this year, Google has announced some changes to the GSoC program for 2022: - Candidate *eligibility* will widen, the only requirement is that candidates are newcomers to open source (instead of "GSoC student", the official term Google uses is now "GSoC contributor"). - The project *effort* can be half-time or full-time - 175 or 350 hours. Everyone submitting at least two project ideas will be asked to *include both half-time and full-time projects*. - Project end dates can be extended (but not moved earlier), at the discretion of the org admin. To keep the administration manageable, *we will only accept projects initially planned for a 12 week duration*. Extensions during the program period will be made on a case-by-case basis. Also, the usual reminder: there is no guarantee that INCF will be accepted as a mentoring organization this year; Google announces the accepted organizations sometime in March. Please be clear with this in your communication with students. The timeline will be similar to the years before, but the dates are not yet set. We expect applications to open early February and close two weeks later (with accepted organizations announced a couple of weeks later). We aim to have a live Project Ideas list from mid January. *Important*: Interested mentors need to contact us (malin at incf.org with CC to gsoc at incf.org) early with a declaration of interest and a short summary of the intended project(s), latest *January 15*. Full project descriptions need to be submitted by *January 25*. ________________________________ Submission instructions Each submission should come by email to malin at incf.org with CC to gsoc at incf.org, and contain: 1) An informative title with relevant keywords (good-to-have: name of tool/project, name of programming language(s) or tools used) 2) A project description including a brief general intro, motivation, aims, scope and skills/skill level needed. Please make sure to clearly state - the planned effort (175 or 350 hours) - the intended skill level (beginner, novice, intermediate, advanced) - the list of pre-requisite skills the contributor will need to have - 2-5 tech keywords (Python, C++, Java, SQL, REST, CUDA, ...) For submissions with two or more project ideas, *please include at least one project of each size (175 or 350 hours)*. 3) At least *one lead mentor + one named co-mentor/backup mentor* who would be able and willing to back the main mentor up in mentoring in case something unforeseen happens. There can be more than one, as long as you are internally clear on who does what. 4) Any planned longer absences during the lead up/student interaction period (February - April) or the project period (May - August), and the plan for covering them. 5) Format: your choice - txt, doc, docx, pdf or a link to a webpage with the full description(s). Anything that can be copied and pasted. *Please note*: Project ideas will be posted on the forum Neurostars.org after the Ideas list goes live, and* prospective mentors are expected to join the forum and be available for questions* from students during the run up to the announcement (late Jan - early March) and the student interactions period (March-April). This can be handled mostly by email, if you prefer, once you have set your NeuroStars account up. Best regards, and happy coding! Malin -- Malin Sandstr?m, PhD Community Engagement Officer malin.sandstrom at incf.org ORCID: 0000-0002-8464-2494 International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels v?g 15 A SE-171 77 Stockholm Sweden http://www.incf.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From donatello.conte at univ-tours.fr Wed Dec 15 04:44:21 2021 From: donatello.conte at univ-tours.fr (Donatello Conte) Date: Wed, 15 Dec 2021 10:44:21 +0100 Subject: Connectionists: DEADLINE EXTENDED: CfP for SS on Graphs for Pattern Recognition: Representations, Theory and Applications at the 3rd ICPRAI in Paris, France Message-ID: <005701d7f198$562c5d30$02851790$@univ-tours.fr> --------------------------------------------------------- Apologies for multiples copies --------------------------------------------------------- Call for Papers Graphs for Pattern Recognition: Representations, Theory and Applications Special Session at the 3rd International Conference on Pattern Recognition and Artificial Intelligence June 1- 3, 2022 https://icprai2022.sciencesconf.org/ Important Dates Paper submission deadline: December 15th, 2021 January 15th, 2022 Author notification: March 8th, 2022 Camera ready deadline: March 22th, 2022 Early bird registration deadline: April 1st, 2022 Time of the conference: June 1st to 3rd, 2022 Scientific Program Committee Isabelle Bloch (FR) Luc Brun (FR) Vincenzo Carletti (IT) Donatello Conte (FR) H. Edelsbrunner (A) Benoit Ga?zere (FR) Rocio Gonzalez-Diaz (Spain) Marco Gori (IT) Yll Haxhimusa (A) Walter G. Kropatsch (A) Xiaoyi Jiang (G) J.Y. Ramel (FR) Luca Rossi (UK) Francesc Serratosa (Spain) Ali Shokoufandeh (US) Mario Vento (IT) Pasquale Foggia (IT) Motivations and topics Graphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological, geometrical, and semantic information. Despite their invaluable descriptive power and their invariance to diverse geometric deformations, their arbitrarily complex structured nature poses serious challenges when they are involved in Pattern Recognition and Artificial Intelligence. Some challenging Problems are: a non-unique representation of data, heterogeneous attributes (symbolic, numeric, etc.), highly complex algorithms like (sub-)graph matching. This Special Session intends to focus on all aspects of graph-based representations in Pattern Recognition and Artificial Intelligence, from theoretical to applications concerns. It spans, but is not limited to, the following topics: ? Dynamic, spatial and temporal graphs ? Graph representations and methods in computer vision ? Geometry and Topology in Graphs ? Graph Neural Networks ? Benchmarks for Graphs in Pattern Recognition ? Graph Learning and Classification ? Graph Matching ? Social Networks Analysis ? Graph Representation Learning Track Chairs Walter G. Kropatsch (TU Wien) Donatello Conte (University of Tours) Vincenzo Carletti (University of Salerno) -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomas.hromadka at gmail.com Wed Dec 15 17:34:49 2021 From: tomas.hromadka at gmail.com (Tomas Hromadka) Date: Wed, 15 Dec 2021 23:34:49 +0100 Subject: Connectionists: COSYNE 2022: Registration; Travel grants Message-ID: <2835abc2-5910-6909-6a10-2ea0b8244378@gmail.com> ==================================================== Computational and Systems Neuroscience 2022 (Cosyne) MAIN MEETING 17 - 20 March 2022 Lisbon, Portugal WORKSHOPS 21 - 22 March 2022 Cascais, Portugal www.cosyne.org ==================================================== IMPORTANT DATES Online registration is now open. Travel grant submission is now open. Travel grant application deadlines *31 December 2021, 11.59PM PST (Undergraduate Travel Grant)* 01 February 2022, 11.59PM PST (Other travel grants) ---------------------------------------------------- COSYNE ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. ----------------------------------------------- TRAVEL GRANTS ----------------------------------------------- Applications are now open for travel grants to attend the conference. Each awardee will receive at least $500 to help offset the costs of travel, registration, and accommodations. Larger grants may be available to those traveling from outside Europe. Special consideration is given to scientists who have not previously attended the meeting, under-represented minorities, students who are attending the meeting together with a mentor, undergraduate students, and authors of submitted Cosyne abstracts. We currently offer five travel grant programs for New Attendees, Presenters, Mentors, Undergraduates, and Childcare travel grants. For details on applying, see www.cosyne.org/travel-grants. COSYNE SPEAKERS Eugenia Chiappe (Champalimaud Centre for the Unknown) Albert Compte (IDIBAPS, Barcelona) Sandeep Robert Datta (Harvard Medical School) Andr? Fenton (New York University) Kate Jeffery (University College London) Ann Hermundstad (Janelia Research Campus, HHMI) Michael A. Long (New York University) Christian Machens (Champalimaud Centre for the Unknown) Asya Rolls (Technion - Israel Institute of Technology) Susanne Schreiber (Humboldt-Universit?t zu Berlin) Maryam Shanechi (University of Southern California) Scott Waddell (University of Oxford) Martha White (University of Alberta) ORGANIZING COMMITTEE General Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Program Chairs: Laura Busse (LMU Munich) and Tim Vogels (IST Austria) Workshop Chairs: Anna Schapiro (U Penn) and Blake Richards (McGill) Tutorial Chair: Kanaka Rajan (Mount Sinai) DEIA Committee: Gabrielle Gutierrez (Columbia) and Stefano Recanatesi (U Washington) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Sashank Pisupati (Princeton) Development Chair: Michael Long (NYU) Social Media Chair: Grace Lindsay (Columbia) Audio-Video Media Chair: Carlos Stein Brito (EPFL) Poster Design: Maja Bialon PROGRAM COMMITTEE Laura Busse (U Munich) Tim Vogels (IST Austria) Athena Akrami (UCL) Omri Barak (Technion) Brice Bathellier (Paris) Bing Brunton (U Washington) Yoram Burak (Hebrew University) SueYeon Chung (Columbia) Christine Constantinople (NYU) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Alexander Ecker (G?ttingen) Tatiana Engel (Cold Spring Harbor) Annegret Falkner (Princeton) Kevin Franks (Duke) Jens Kremkow (Berlin) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Emilie Mace (MPI Neurobiology) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Jill O'Reilly (Oxford) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montr?al) Yiota Poirazi (FORCE) Nathalie Rochefort (Edinburgh) Cristina Savin (NYU) Daniela Vallentin (MPI Ornithology) Brad Wyble (Penn State) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See www.cosyne.org/mailing-lists for details. From terry at salk.edu Wed Dec 15 09:49:24 2021 From: terry at salk.edu (Terry Sejnowski) Date: Wed, 15 Dec 2021 06:49:24 -0800 Subject: Connectionists: 2021 Misha Mahowald Prize for Neuromorphic Engineering In-Reply-To: Message-ID: The 2021 Misha Mahowald Prize for Neuromorphic Engineering awards were announced on Friday Dec 12 2021 to two teams of researchers who used neuromorphic principles to build devices that help disabled humans improve sensory and motor interaction with the world: https://urldefense.com/v3/__https://www.mahowaldprize.org/prize-awards/prize-2021__;!!GX6Nv3_Pjr8b-17qtCok029Ok438DqXQ!mmtY127OiWX1rL6fpNzUd64Lm1mKBCWpbq8cDILcCDcj31D-kC_tqRkzfqfEoQ$ Terry ----- From rpaudel142 at gmail.com Wed Dec 15 21:59:34 2021 From: rpaudel142 at gmail.com (Ramesh Paudel) Date: Wed, 15 Dec 2021 21:59:34 -0500 Subject: Connectionists: CFP Reminders - (SaT-CPS 2022) ACM Workshop on Secure and Trustworthy Cyber-Physical Systems Message-ID: Dear Colleagues, *** Please accept our apologies if you receive multiple copies of this CFP *** Please consider submitting and/or forwarding to the appropriate groups/personnel the opportunity to submit to the ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (SaT-CPS 2022), which will be held in Baltimore-Washington DC area (or virtually) on April 26, 2022 in conjunction with the 12th ACM Conference on Data and Application Security and Privacy (CODASPY 2022). *** Paper submission deadline: December 30, 2021 *** *** Website: https://sites.google.com/view/sat-cps-2022/ *** SaT-CPS aims to represent a forum for researchers and practitioners from industry and academia interested in various areas of CPS security. SaT-CPS seeks novel submissions describing practical and theoretical solutions for cyber security challenges in CPS. Submissions can be from different application domains in CPS. Example topics of interest are given below, but are not limited to: Secure CPS architectures - Authentication mechanisms for CPS - Access control for CPS - Key management in CPS - Attack detection for CPS - Threat modeling for CPS - Forensics for CPS - Intrusion and anomaly detection for CPS - Trusted-computing in CPS - Energy-efficient and secure CPS - Availability, recovery, and auditing for CPS - Distributed secure solutions for CPS - Metrics and risk assessment approaches - Privacy and trust - Blockchain for CPS security - Data security and privacy for CPS - Digital twins for CPS - Wireless sensor network security - CPS/IoT malware analysis - CPS/IoT firmware analysis - Economics of security and privacy - Securing CPS in medical devices/systems - Securing CPS in civil engineering systems/devices - Physical layer security for CPS - Security on heterogeneous CPS - Securing CPS in automotive systems - Securing CPS in aerospace systems - Usability security and privacy of CPS - Secure protocol design in CPS - Vulnerability analysis of CPS - Anonymization in CPS - Embedded systems security - Formal security methods in CPS - Industrial control system security - Securing Internet-of-Things - Securing smart agriculture and related domains The workshop is planned for one day, April 26, 2022, on the last day of the conference. Instructions for Paper Authors All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal. All papers must be submitted electronically via the Easychair system: https://easychair.org/conferences/?conf=acmsatcps2022 Full-length papers Papers must be at most 10 pages in length in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template). Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM Digital Library. The presenter must register for the workshop before the deadline for author registration. Position papers and Work-in-progress papers We also invite short position papers and work-in-progress papers. Such papers can be of length up to 6 pages in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template), and must clearly state "Position Paper" or "Work in progress," as the case may be in the title section of the paper. These papers will be reviewed and accepted papers will be published in the conference proceedings. Important Dates Due date for full workshop submissions: December 30, 2021 Notification of acceptance to authors: February 10, 2022 Camera-ready of accepted papers: February 20, 2022 Workshop day: April 26, 2022 *- - - - - - - - - - -* *Ramesh Paudel, Ph.D.* Publicity and Web Co-Chair Research Scientist George Washington University Washington, DC. -------------- next part -------------- An HTML attachment was scrubbed... URL: From juyang.weng at gmail.com Wed Dec 15 19:01:24 2021 From: juyang.weng at gmail.com (Juyang Weng) Date: Wed, 15 Dec 2021 19:01:24 -0500 Subject: Connectionists: Call for Applications: BMI Machine Conscious Learning Project Message-ID: *BMI Machine Conscious Learning Project* http://www.brain-mind-institute.org/program-summer.html Ever since humankind came into being, holistic mechanisms of Natural General Intelligence (NGI) and Artificial General Intelligence (AGI) have been elusive. For example, the Third World Science and Technology Development Forum Nov. 6-7, 2021 published "The Ten Scientific Problems for the Development of Human Society for 2021". The No. 1 Problem in the information domain is "what are the mechanisms for human brains to process information and for generating human intelligence?" Many machine learning experts hoped that NGI and AGI can be modeled by, or achieved by, training increasingly larger neural networks on increasingly larger data sets that are static, like well-known projects AlphaGo, AlphaZero, AlphaFold , the IBM Debater and many other similarly large neural network projects elsewhere. Unfortunately, such approaches are categorically hopeless for AGI, not only because of the alleged Post Selection protocol flaws [ WengNatureProtocol21 ,WengScienceProtocol21 ] but something much deeper and more fundamental. The recent discovery of Conscious Learning by Weng 2022 [WengCLICCE22 ,WengCLAIEE22 ] revealed a surprising principle, namely consciousness is recursively necessary across every time instant of learning by humans and machines in order to reach their NGI and AGI at each corresponding mental age. Consciousness, in the full sense as we know it and defined in dictionaries, will never arise as an outcome of feeding static data sets, regardless of how large the data sets are and what kinds of neural network we use. But instead, consciousness is a necessary capability of a learner, natural or artificial for NGI or AGI, so that conscious thinking takes place while the learner processes information while learning across space and time on the fly. Weng proposes that the algorithmic theory of Conscious Learning in [ WengCLICCE22 ,WengCLAIEE22 ] supported by the Developmental Networks is the first holistic solution to the above No. 1 Problem in the information domain. Therefore, GNI appears to be computationally modeled and AGI seems to be machine achievable. The remaining challenges toward modeling NGI and achieving AGI are still great but exciting. They include education of Conscious Learning theory and algorithms; research on hardware design for real-time, brain size Conscious Learning; development of practical Conscious Learning products; and applications of Conscious Learning theory and algorithms. BMI, the Brain-Mind Institute, is pleased to announce a funded Project, called BMI Conscious Machine Learning Project, for all those who are interested. This announcement calls for professors, graduate students, and undergraduate students to apply for an appropriate position in the Project. The open positions include the following three categories: 1. *Research advisors*: There are four categories, assistant professors, associate professors, full professors and retired professors, corresponding to your current rank. The responsibilities include advising local students. It is desirable that each professor recruits a few of his students locally. Send your CV to BMI with the names, affiliations and contact information of the students who will submit applications in association with you. Each BMI paid student will correspond a part of budget for his research advisor. 2. *Graduate students: *There are two categories, PhD program and MS program. Each student is expected to spend 10 hours each week during his university semesters and 40 hours each week during summer. The student's time spent on the projects will be paid by BMI at a rate suited for his own country. Each applicant should identify a local research advisor who supervises the project on a weekly basis. If you are a graduate student in a university and are interested in applying for the Project, find a professor in your local university who can supervise you. Ask him to jointly apply for a professor position at the Project. You two should name each other in the applications. Send your CV and official transcripts during the undergraduate years and the graduate years. 3. *Undergraduate students: *There are four categories, freshmen, sophomore, junior and senior, corresponding to your year in your home university. Other requirements are similar to the Graduate student category. Admission terms: summer session 2022 or fall 2022. Specify your preferred starting summer date and fall date, as each country has a different date. Send your filled application form , your application and supporting material to juyang.weng at gmail.com with a subject: Application: BMI Conscious Machine Learning Project. *Important dates:* *January 15, 2022:* Deadline for application *March 15, 2022:* Notice of admission For further detail and questions, contact juyang.weng at gmail.com. PDF file -- Juyang (John) Weng -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASIM.ROY at asu.edu Thu Dec 16 14:59:34 2021 From: ASIM.ROY at asu.edu (Asim Roy) Date: Thu, 16 Dec 2021 19:59:34 +0000 Subject: Connectionists: Call for Papers - Cognitive Computation Special Issue - "How the brain works: Where are we now and what remains to be learned?" - Submission Deadline - Jan 31, 2022 Message-ID: Dear Colleagues, This Special Issue is about stepping back and taking a look at where we are in terms of understanding the brain. We want to publish short position papers, maximum 10 pages long. We are aiming for quick reviews, about two weeks. Further details are provided below. Asim Roy Professor, Information Systems Arizona State University Asim Roy | iSearch (asu.edu) Lifeboat Foundation Bios: Professor Asim Roy ------------------------------------------------------------------------------------------------------------------------------ Springer's Cognitive Computation journal (http://springer.com/12559) Special Issue Call for Papers: How the brain works: Where are we now and what remains to be learned? Guest Editors: (Lead) Asim Roy, Arizona State University, USA, E-mail: ASIM.ROY at asu.edu Claudius Gros, Institute for Theoretical Physics, Goethe University Frankfurt, Germany, E-mail: gros at itp.uni-frankfurt.de Juyang Weng, Michigan State University, USA, E-mail: weng at cse.msu.edu Jean-Philippe Thivierge, University of Ottawa, Canada, E-mail: Jean-Philippe.Thivierge at uottawa.ca Tsvi Achler, Optimizing Mind, Email: achler at optimizingmind.com Ali A. Minai, University of Cincinnati, USA, E-mail: Ali.Minai at uc.edu Aim and Motivation: Arguments about the brain and how it works are endless. Despite some conflicting conjectures and theories that have existed for decades without resolution, we have made significant progress in creating brain-like computational systems to solve some important engineering problems. It would be a good idea to step back and examine where we are in terms of our understanding of the brain and potential problems with the brain-like systems that have been successful so far. For this special issue of Cognitive Computation, we invite thoughtful articles on some of the issues that we have failed to address and comprehend in our journey so far in understanding the brain. We aim for rapid peer-reviews by experts (about two weeks) for all selected submissions and plan to publish the special issue papers on a rolling basis from early 2022. Topics: We plan to publish a collection of short articles on a variety of topics that could be asking new questions, proposing new theories, resolving conflicts between existing theories, and proposing new types of computational models that are brain-like. Deadlines: SI submissions deadline: 31 January 2022 First notification of acceptance: 21 February 2022 Submission of revised papers: 10 March 2022 Final notification to authors: 31 March 2022 Publication of SI: Rolling basis (2022) Submission Instruction: Prepare your paper in accordance with the Journal guidelines: www.springer.com/12559. Submit manuscripts at: http://www.editorialmanager.com/cogn/. Select "SI: How the Brain Works" for the special issue under "Additional Information." Your paper must contain significant and original work that has not been published nor submitted to any journals. 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URL: From franciscocruzhh at gmail.com Thu Dec 16 15:36:12 2021 From: franciscocruzhh at gmail.com (Francisco Cruz) Date: Thu, 16 Dec 2021 17:36:12 -0300 Subject: Connectionists: [CfP] ALA2022: Adaptive and Learning Agents Workshop 2022 Message-ID: ALA2022: Adaptive and Learning Agents Workshop 2022 Auckland, New Zealand, May 9-10, 2022 (Virtual) Workshop website: https://ala2022.github.io/ Submission link: https://easychair.org/conferences/?conf=ala20220 Adaptive and Learning Agents Workshop at AAMAS (Auckland, New Zealand) https://ala2022.github.io/ Submission deadline: January 30, 2022 Extended versions of all original contributions at ALA 2022 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 5.606). ******************************************************* TL;DR: * Workshop with a long and successful history, now in its thirteenth edition. * Covering all aspects of adaptive and learning agents and multi-agent systems research. * Open to original research papers, work-in-progress, and visionary outlook papers, as well as presentations on recently published journal papers. * ACM proceedings (AAMAS) format up to 8 pages (excluding references) for original research, up to 6 pages for work-in-progress and outlook papers (shorter papers are also welcome and will not be judged differently) and 2 pages for recently published journal papers. * Accepted papers are eligible for inclusion in a post-proceedings journal special issue. * Submissions through easychair: https://easychair.org/my/conference?conf=ala20220 ******************************************************* IMPORTANT DATES: * Submission Deadline: January 30, 2022 * Notification of acceptance: February 27, 2022 * Camera-ready copies: March 5, 2022 * Workshop: May 9 & 10, 2022 * Journal submission deadline: September 15, 2022 ******************************************************* OVERVIEW Adaptive and learning agents, particularly those interacting with each other in a multi-agent setting, are becoming increasingly prominent as the size and complexity of real-world systems grows. How to adaptively control, coordinate and optimize such systems is an emerging multi-disciplinary research area at the intersection of Computer Science, Control Theory, Economics, and Biology. The ALA workshop will focus on agents and multi-agent systems which employ learning or adaptation. The goal of this workshop is to increase awareness of and interest in adaptive agent research, encourage collaboration and give a representative overview of current research in the area of adaptive and learning agents and multi-agent systems. It aims at bringing together not only scientists from different areas of computer science but also from different fields studying similar concepts (e.g., game theory, bio-inspired control, mechanism design). All aspects of adaptive and learning agents and multi-agent systems are on topic for this workshop, but we will particularly encourage work that modifies established learning techniques and/or creates new learning paradigms to address the many challenges presented by complex real-world problems. The topics of interest include (but are not limited to): * Novel combinations of reinforcement and supervised learning approaches * Integrated learning approaches using reasoning modules like negotiation, trust, coordination, etc. * Supervised and semi-supervised multi-agent learning * Reinforcement learning in multi-agent systems * Novel deep learning approaches for adaptive single and multi-agents systems * Human-in-the-loop learning systems * Planning and Reasoning (single and multi-agent) * Distributed learning * Adaptation and learning in dynamic environments * Evolution and Co-evolution of agents in complex multi-agent environments * Cooperative exploration * Learning to cooperate and collaborate * Learning trust and reputation * Communication restrictions and their impact on multi-agent coordination * Design of reward structure and fitness measures for coordination * Scaling learning techniques to large systems of agents * Emergent behavior in adaptive multi-agent systems * Game theoretical analysis of adaptive multi-agent systems * Neuro-control for adaptation in multi-agent systems * Bio-inspired multi-agent systems * Adaptive and learning agents for multi-objective decision making * Multiple objectives in (multi-)agent systems * Applications of adaptive and learning (multi-agent) systems to model real world complex systems In addition to these topics, this year we are interested in exploring negative results that can serve as guidelines for early-stage researchers in the field of adaptive and learning single/multi-agent systems. ******************************************************* SUBMISSION DETAILS Papers can be submitted through EasyChair: https://easychair.org/my/conference?conf=ala20220 We invite submission of original work, up to 8 pages in length (excluding references) in the ACM proceedings format (i.e. following the AAMAS formatting instructions). This includes work that has been accepted as a poster/extended abstract at the AAMAS 2022 conference. Additionally, we welcome submission of preliminary results, i.e. work-in-progress, as well as visionary outlook papers that lay out directions for future research in a specific area, both up to 6 pages in length, although shorter papers are very much welcome, and will not be judged differently. Finally, we also accept recently published journal papers in the form of a 2 page abstract. All submissions will be peer-reviewed (single-blind). Accepted work will be allocated time for poster and possibly oral presentation during the workshop. Extended versions of all original contributions at ALA 2022 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 5.606). Deadline for submitting extended papers: September 15, 2022. We look forward to receiving your submissions, - The Organizers Conor F. Hayes (NUI Galway, IE) Francisco Cruz (Deakin University, AUS) Fernando P. Santos (University of Amsterdam, NL) Felipe Leno da Silva (Lawrence Livermore National Lab, USA) ================================================================== -------------- next part -------------- An HTML attachment was scrubbed... URL: From R.I.J.Dobbe at tudelft.nl Thu Dec 16 15:49:04 2021 From: R.I.J.Dobbe at tudelft.nl (Roel Dobbe) Date: Thu, 16 Dec 2021 20:49:04 +0000 Subject: Connectionists: [Call for Workshops] 1st Hybrid Human-AI Conference - deadline January 31 In-Reply-To: References: Message-ID: Dear friends and colleagues, We are excited to share with you the Call for Workshops for the First Hybrid Human-Artificial Intelligence (HHAI) Conference. We welcome workshop proposals on a broad range of topics related to HHAI with the aim to open up conversations that cross disciplinary boundaries and bring together diverse stakeholders and perspectives. As a first edition, the workshops will be crucial in building a diverse and open community, which will provide input to how we shape the conference moving forward. We therefore welcome both traditional workshop formats as well as creative and reflective events that push the boundaries of existing fields and epistemologies. Join us in shaping the HHAI community and send in your proposals by January 31 ? see further guidelines, timeline and information below or via EasyChair. We also appreciate if you forward this call to colleagues you deem interested to contribute to this program. Please also invite non-academic enthusiasts that are engaging with HHAI topics. Thank you and please feel welcome to ask us any questions. On behalf of the HHAI team, Kindly, Ana Valdivia and Roel Dobbe (Workshop Chairs) _________________________ Call for Workshops Hybrid Human-Artificial Intelligence (HHAI) is the first international conference focusing on the study of Artificial Intelligent systems that integrate synergistically, purposefully and responsibly with human activity, amplifying instead of replacing human intelligence and interaction. The first International Conference on Hybrid Human-Artificial Intelligence (#HHAI2022, http://www.hhai-conference.org) will be held in Amsterdam on June 13-17, 2022. HHAI-2022 workshops will provide a platform for discussing Hybrid Human-Artificial Intelligence in more informal settings and for a broad audience. We invite proposals for full-day and half-day events during the two days leading up to the main conference. Registration for the main conference is expected, arrangements for non-traditional conference attendees can be requested. The goal of workshops is to bring together academics, professionals and users of technology to better understand the socio-technical benefits, risks and limitations that artificial intelligence has when interacting with humans from different perspectives. Thus we encourage workshops presenting broad concepts of human-artificial intelligence interaction or specific cases. We invite submissions for events that foster cross-disciplinary interaction, scientific discourse, and creative and critical reflection, rather than just being mini-conferences. To do so, we offer organizers flexibility for format that best suit the goals of their event. We especially welcome submissions of communities that are usually not featured prominently in artificial intelligence events and conferences. Important Dates * January 31, 2022: Workshop proposals due via EasyChair (https://easychair.org/my/conference?conf=hhai2022wt#). * February 7, 2022: Workshop proposal acceptance notification * February 14, 2022: Deadline for announcing the Workshops Call for Papers/Contributions * April 1, 2022: Workshop application deadline for contributions to the workshop * April 29, 2022: Recommended deadline for paper acceptance notification * June 13,14 2022: HHAI2022 Workshops * August 31, 2022 (optional): Deadline workshop report Submission guidelines Proposals should consist of 4 pages (+ references) and must include the following information: * Title and abstract of the workshop. * Name, affiliations, short bio and email address of each member of the team. The names and full contact information (email, postal addresses, and telephone numbers) of the organizing committee ? a minimum of three people knowledgeable in the field-and short descriptions of their relevant expertise and how it complements each other. (Please specify a main contact.) Strong proposals include organizers who bring differing perspectives to the workshop topic and who are actively connected to the communities of potential participants. * A description of the workshop topic. Identify the specific topics and issues on which the workshop will focus. * A brief discussion of why the topic is of particular interest at this time, including a discussion of prior workshops in this area (if applicable). * A brief description of the proposed workshop format, regarding the mix of events such as paper presentations, invited talks, panels, and general discussion. * A brief description of the (intended) presenters/contributors to the event. * An indication as to whether the workshop should be considered for a half-day or full-day event. * The targeted audience size. * Additional artifacts (optional): If you have additional materials which would support your proposal, such as a video example of the facilitation, a website, or written workbooks, you can also include that in your proposal. * Documentation and reporting plans (optional): We would like to give the opportunity for sessions to be properly documented. Indicate how you plan to capture and/or catalyze ideas that arise in your session (e.g., mention format and technical infrastructure for documentation during the event). We plan to compile artifacts for sessions that choose this (max 1000 words), and publish them on a microsite, linked to the HHAI website >. Deadlines for reports to be included are August 31, 2022?. * Publicity plans: If you plan to use social media to promote or document your session, please indicate a hashtag here. * References or citations (if applicable). * Other needs: Include a note if you have any special requirements for your session that are not addressed elsewhere. Evaluation criteria * Relevance: Connection to and relevance for the objectives of the HHAI conference and the objectives listed in this particular call. * Rigor and quality: The potential of the proposal to generate stimulating discussions and useful results about scientific and socio-technical problems regarding the interaction of artificial intelligence and human activity. * Organization: Is the plan clear, sensible and thorough? * Diversity and Inclusion: Thoughtfulness in the approach detailed to ensure engagement and participation of a broad audience. Diversity in backgrounds of the workshop organisers and intended presenters/contributors. Workshops - Topics of Interest We welcome two types of contributions: traditional and creative workshops. Traditional workshops typically match the topics and different challenges of the general call for contributions for the Hybrid Human-Artificial Intelligence Conference. Creative workshops invite non-conventional contributions with different formats (e.g. unconference, interactive workshops or art exhibitions) with topics related to the conference. Traditional Workshops For traditional workshops, organizers may consider a call for papers and a set of invited talks around a certain theme (with or without papers). The topics may be inspired by those listed for the broader conference, including adaptive human AI, co-learning and co-creation, fair, ethical, responsible and trustworthy AI, socio-technical system perspectives, law and policy (see a more exhaustive list here). We welcome workshops related to all types of technology and application domains. Creative and Reflective Events Recently, calls for human-centered AI have intensified, evidenced by the need for ?appropriate human control? in the European Commission?s proposal for AI regulation and many new research programs exploring the intersection of AI technology and human activity. While AI offers many new opportunities, it also brings new risks for human flourishing. A number of prominent studies acknowledge that properly understanding the risks and opportunities of AI systems and human-AI interactions require more holistic approaches. In the spirit of reflection and community-building, we invite academics of all disciplines and people representing different communities of practice (including journalism, advocacy, activism, organizing, education, art, law and policy) to contribute with creative and reflective programming. This part of the conference considers contributions to: 1. Creatively engage with and address critiques of the field of human-centered AI -- its gaps, omissions, and possibilities by taking a more holistic approach; 2. Highlight novel modes of interaction with questions of human-centered AI; 3. Invite an interdisciplinary and cross-practice group of organizers, researchers, activists, and artists to explore and inspire conversation and open future lines of research, collaboration, and practice; 4. Push beyond the epistemological and methodological boundaries of their practice. The format is flexible and can be chosen to best address the above goals. Alternative formats include but are not limited to: ? Lightning Talks, ? Debates or Rump Sessions, ? Poster and/or Demo Session, ? Unconference, ? Interactive Workshop, ? Art Exhibit or Other Artistic Intervention. We understand that for some communities, conference attendance may be more challenging to finance and make time for. We therefore encourage you to consider forms of support for contributors. The conference organization is open to consider how we can make attendance easier for groups with limited resources. Building a safe and inclusive culture together The first edition of the HHAI workshops and broader conference offers an opportunity to build culture together, which we aim to do in a mindful manner. The conference spins out of the Hybrid Intelligence Centre, which has embraced diversity and inclusion as a central principle in how we recruit and how we interact with each other. We will build a safe and inclusive culture together with the workshop organizers. This will be reflected in our assessment of the proposals. Here we welcome your suggestions for ensuring a welcoming program for people from different backgrounds, both professionally and individually. In the assessments of the proposals, we will have experts providing suggestions for strengthening the plans. After selection, we will propose a set of guidelines and shape these with all workshop organizers, so that we learn and exchange best practices and work towards a shared mindset for making the workshops a success. On a more formal note, we also know that many members of our community may have been subject to discrimination and harassment in our work as researchers/professionals, including at conferences. The HHAI organising committee is committed to making HHAI2022 as safe, diverse and tolerant as possible and building a lasting culture of inclusivity. This means we will do what is in our abilities to protect people who may be subject to discrimination or harassment, and we maintain open to any questions or suggestions abour our ways of communicating and organizing. Chairs: * Roel Dobbe, Delft University of Technology (Workshop Co-chair) * Ana Valdivia, King?s College London (Workshop Co-chair) * Stefan Schlobach, Vrije Universiteit Amsterdam (General Chair) -------------- next part -------------- An HTML attachment was scrubbed... URL: From john.murray at yale.edu Thu Dec 16 16:48:09 2021 From: john.murray at yale.edu (Murray, John) Date: Thu, 16 Dec 2021 21:48:09 +0000 Subject: Connectionists: Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University Message-ID: Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University The Swartz Program for Theoretical Neuroscience at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date in 2022. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories affiliated with the Swartz Program at Yale (Jessica Cardin, Michael Crair, Damon Clark, Jonathan Demb, George Dragoi, Thierry Emonet, Michael Higley, Joe Howard, Monika Jadi, Jamie Jeanne, Alfred Kaye, Liang Liang, Benjamin Machta, John Murray, Anirvan Nandy, Ilker Yildririm, Steven Zucker). Applicants will be encouraged to participate in neuroscience and quantitative biology community at Yale, including through the Wu-Tsai Institute (https://wti.yale.edu/) and the Quantitative Biology Institute (https://qbio.yale.edu/). Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a CV, selected (p)reprints, contact information for two or three references, and a statement of research interests including which laboratories at Yale are of interest. All application materials should be sent to the following e-mail address with "Swartz" in the email title: john.murray at yale.edu. Review of applications will begin January 1, 2022 and continue until a position is filled. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. https://neurojobs.sfn.org/job/32853/postdoctoral-swartz-fellowship-positions-in-theoretical-and-computational-neuroscience-at-yale/ John D. Murray ----------------------------------------------- Associate Professor of Psychiatry, Physics, and Neuroscience Yale University murraylab.yale.edu ----------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From watanabe at sys.t.u-tokyo.ac.jp Fri Dec 17 01:30:11 2021 From: watanabe at sys.t.u-tokyo.ac.jp (=?UTF-8?B?5rih6YKJIOato+WzsA==?=) Date: Fri, 17 Dec 2021 15:30:11 +0900 Subject: Connectionists: =?utf-8?q?=E3=80=90Call_for_Free_Online_Participa?= =?utf-8?q?tion=E3=80=91_Mechanism_of_Brain_and_Mind?= Message-ID: Dear Colleague, We are pleased to announce our 21st international workshop, Mechanism of Brain and Mind ?Complex cognition and decision-making? January 12, 2022 http://brainmind.umin.jp/eng-wt21.html free registration: https://oist.zoom.us/webinar/register/WN_EAwmbeF6SVShSlfsEH6w6w registration deadline: January 7, 2022 Following our tradition of holding the workshop at a cozy ski resort in Hokkaido,Japan, you will have plenty of time to interact with our speakers. (10 mins question + 30 mins breakout session) I hope to see you there and also at our physical meetings in the following years! January 12 Morning Session 9:10-10:00 (JST) Shogo Ohmae (Baylor College of Medicine) 10:00-10:30 (JST) Breakout Session 10:40-11:30 (JST) Hidenori Tanaka (Physics & Informatics Lab, NTT Research) 11:30-12:00 (JST) Breakout Session Afternoon Session 14:00-14:50 (JST) Mingbo Cai (The University of Tokyo International Research Center for Neurointelligence) 14:50-15:20 (JST) Breakout Session 15:30-16:20 (JST) Tianming Yang (Chinese Academy of Sciences) 16:20-16:50 (JST) Breakout Session Best Regards, Masataka Watanabe Vice Chairman, Workshop on the Mechanism of Brain and Mind Associate Professor, School of Engineering, University of Tokyo -------------- next part -------------- An HTML attachment was scrubbed... URL: From malini.vinita.samarasinghe at ini.rub.de Fri Dec 17 07:16:39 2021 From: malini.vinita.samarasinghe at ini.rub.de (Vinita Samarasinghe) Date: Fri, 17 Dec 2021 13:16:39 +0100 Subject: Connectionists: Postdoc position - Cheng Lab - Ruhr University Bochum Message-ID: <98be461e-9150-0f70-e022-76e9a0eb9c26@ini.rub.de> Prof. Sen Cheng, Institute for Neural Computation at the Ruhr University Bochum, invites applications for a full time *Postdoctoral position* (TV-L E13) in Computational Neuroscience. The position starts on July 1, 2022 and is funded for three years. The successful applicant will work on a collaborative project (within the Collaborative Research Center ?Extinction Learning? (SFB 1280 )), together with experimentalists to: * analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280, * compare the learning dynamics between individuals, species, learning phases and learning paradigms, * develop algorithms to analyze the learning dynamics, * develop and study computational models of learning dynamics, * coordinate research with other participating projects. Candidates must have: * a doctorate degree in neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field, * relevant experience in mathematical modeling, * excellent programming skills (e.g., Python, C/C++, Matlab), * excellent communication skills in English, * the ability to work well in a team. Research experience in neuroscience would be a further asset. The position is third party funded and does not have any formal teaching duties attached. The research group is highly dynamic and uses diverse computational modeling approaches including biological neural networks, cognitive modeling, and machine learning to investigate learning and memory in humans and animals. For further information see www.rub.de/cns. The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics. The Institute for Neural Computation focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. Please send your application, including CV, transcripts and research statement electronically, as a *single PDF file*, to *samarasinghe at ini.rub.de*. In addition, at least two academic references must be sent independently to the above email address. The deadline for applications is *January 2, 2022*. Travel costs for interviews will not be reimbursed. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to network with them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. If you have any questions please feel free to get in touch with Vinita Samarasinghe (contact below) -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, NB 3/73 Postfachnummer 110 Universit?tstr. 150 44801 Bochum Germany Tel: +49 (0) 234 32 27996 Email:samarasinghe at ini.rub.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From pmasulli at e-nns.org Fri Dec 17 08:00:56 2021 From: pmasulli at e-nns.org (Paolo Masulli ENNS) Date: Fri, 17 Dec 2021 14:00:56 +0100 Subject: Connectionists: CFP 31st International Conference on Artificial Neural Networks ICANN 2022, Sept 6-9, Bristol, UK - Hybrid event Message-ID: <2790d76e-a69d-f08b-e96c-77ff10c291fa@e-nns.org> 31st International Conference on Artificial Neural Networks ICANN 2022 https://e-nns.org/icann2022 Bristol, United Kingdom - *Hybrid event* 6 - 9 September 2022 ============================================================= The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2022 the Department of Computer Science and Creative Technologies of the University of the West of England, in Bristol, United Kingdom will organise ICANN 2022. This will be held at Frenchay Campus from 6 to 9 September 2022. The conference is currently planned as a *hybrid event* with some presence and some online participation if possible. We will continuously monitor the situation in the next few months according to the overall health developments. * **CONFERENCE TOPICS* ICANN 2022 is a conference featuring tracks in Brain-inspired Computing and Machine Learning in Artificial Neural Networks, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: *Machine Learning*: Deep Learning, Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information-theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models, Recurrent Networks, Ethics of AI. *Brain-inspired Computing*: Cognitive models, Computational Neuroscience, Self-organisation, Bioinspired Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Cognitive Neuroscience, Brain Informatics, Perception and Action. *Neural Applications for*: Bioinformatics, Biomedicine, Intelligent Robotics, Neurorobotics, Language Processing, Speech and Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. *CALL FOR CONTRIBUTED SCIENTIFIC COMMUNICATIONS* All scientific communications presented at ICANN 2022 will be reviewed and scientifically evaluated by a panel of experts. The conference will feature two categories of communications: - oral communications (15'+5') - poster communications. *Call for Special Sessions and Workshops* ICANN 2022 organizers cordially invite internationally recognised experts to organise Special sessions and Workshops within the general scope of the conference. Proposals should be sent to ICANN2022 at uwe.ac.uk *CALL FOR PAPERS* Authors willing to present original contributions in either the oral or poster category may submit: - A full paper of maximum 12 pages (including references) to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series with individual DOI. - An extended abstract of maximum 4 pages to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series, without indexing. The number of oral slots is limited. In case the number of requested oral presentations is larger than the available slots, the ICANN scientific committee will select which papers will be reassigned to a poster session. This selection will be based on the coherence of the programme and is totally independent of the category of submission. Submission of communications will be on the conference website: https://e-nns.org/icann2022/ *IMPORTANT DATES* Deadline for special session and workshop proposals: 28 Feb 2022 Opening of contribution submissions: 21 Feb 2022 Deadline for full paper and extended abstract submission: 3 Apr 2022 Notification of acceptance: 10 Jun 2022 Camera-ready paper upload: 30 June 2022 Deadline for author registration and early registration at early rate: 30 June 2022 *BEST PAPER AWARDS* ENNS will sponsor a maximum of four best paper awards. All awards will be presented during the final ceremony. *TRAVEL GRANTS* The European Neural Network Society sponsors a number of Student Travel Grants covering part of the costs for attending ICANN. Details will be provided on the conference website. *ORGANISATION* *General Chairs* Elias Pimenidis ? UWE Bristol, UK Angelo Cangelosi ? University of Manchester, UK *Organising Committee Chairs* Tim Brailsford ? UWE Bristol, UK Larry Bull ? UWE Bristol, UK *Honorary Chairs* Stefan Wermter ? University of Hamburg, Germany (ENNS President) Igor Farka? ? FMPI, Comenius University in Bratislava, Slovakia *Programme Committee Chairs* Plamen Angelov ? Lancaster University, UK Mehmet Aydin ? UWE Bristol, UK Chrisina Jayne ? Teesside University, UK Elias Pimenidis ? UWE Bristol, UK *Communication Chairs* Paolo Masulli ? ENNS, Technical University of Denmark Krist?na Malinovsk? ? FMPI, Comenius University in Bratislava, Slovakia Antonios Papaleonidas ? Democritus University of Thrace, Greece -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: hjLRcgejvH35bOQV.png Type: image/png Size: 9597 bytes Desc: not available URL: From helma.torkamaan at uni-due.de Fri Dec 17 08:06:40 2021 From: helma.torkamaan at uni-due.de (Helma Torkamaan) Date: Fri, 17 Dec 2021 14:06:40 +0100 Subject: Connectionists: ACM UMAP 2022 : First Call for Workshop and Tutorial Proposals Message-ID: Please accept our apologies in case of multiple receptions. Please send it to interested colleagues. -------------------------------------------------------- # **30th ACM International Conference on User Modeling, Adaptation and Personalization (ACM UMAP'22)** Barcelona, Spain, and Online 4 - 7 July 2022 https://www.um.org/umap2022/ Proposal Submission Deadline: January 27, 2022 -------------------------------------------------------- **BACKGROUND AND SCOPE** ============================ **ACM UMAP'22** is pleased to invite proposals for workshops and tutorials to be held in conjunction with the conference. ACM UMAP is the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users, and which collect, represent, and model user information. We encourage both researchers and industry practitioners to submit workshop and tutorial proposals. We strongly suggest involving organizers from different institutions, bringing different perspectives to the workshop or tutorial topic. We welcome workshops and tutorials with a creative structure that may attract various types of attendees and ensure rich interactions. All the tutorials and workshops should support both virtual and physical attendance (although we hope physical to be the preferred option). -------------------------------------------------------- **Call for Workshop Proposals** ============================ The workshops provide a venue to discuss and explore emerging areas of User Modeling and Adaptive Hypermedia research with like-minded researchers and practitioners from industry and academia. -------------------------------------------------------- **Important Dates** ============================ - Proposals due: January 27, 2022 - Notification to proposers: February 10, 2022 - Workshop day(s): July TBD, 2022 All deadlines are 11:59 pm, AoE time (Anywhere on Earth). -------------------------------------------------------- **Workshop Formats** ============================ In this edition, our goal is to have a balanced workshop program, comprising workshops with different formats and addressing newly emerging, currently evolving and established research topics. Different schemas to organize the workshop are possible, such as: - Working group meetings around a problem or topic. - Mini-conferences on special topics, having their own paper submission and review processes. - Mini-competitions or challenges around selected topics with individual or team participation. - Interactive discussion meetings focusing on subtopics of the UMAP general research topics. - Joint panels for different workshops. The detailed instructions for the proposal content, the submission, the responsibilities, the proceedings and the registration are provided at https://www.um.org/umap2022/call-for-workshops/. -------------------------------------------------------- **Call for Tutorial Proposals** ============================ Tutorials are intensive instructional sessions that provide a comprehensive introduction to established or emerging research topics of interest for the UMAP community. -------------------------------------------------------- **Important Dates** ============================ - Proposals due: January 27, 2022 - Notification to proposers: February 10, 2022 - Tutorial day: July TBD, 2022 All deadlines are 11:59 pm, AoE time (Anywhere on Earth). -------------------------------------------------------- **Tutorial Topics** ============================ An ideal tutorial should be broad enough to provide a basic introduction to the chosen area, but it should also cover the most important topics in depth. Topics of interest include, but are not limited to: - New user modeling technologies, methods, techniques, and trends (e.g., exploiting data mining and big data analytics for user modeling, evaluation methodologies, data visualization, etc.). - User modeling and personalization techniques for specific domains (e.g., health, e-government, e-commerce, cultural heritage, education, internet of things, mobile, music, information retrieval, human-robot interaction etc.). - Application and impact of the user modeling and personalization techniques for information retrieval and recommender systems, including beyond-accuracy aspects (e.g., fairness). - Eliciting and learning user preferences by taking into account users'; emotional state, physical state, personality, trust, cognitive factors. The detailed instructions for the proposal content, the submission, the responsibilities, the proceedings and the registration are provided at https://www.um.org/umap2022/call-for-tutorials/. -------------------------------------------------------- **Workshop and Tutorial Chairs** ============================ - Mirko Marras, University of Cagliari, Italy - Elvira Popescu, University of Craiova, Romania - Contact: [umap2022-wt at um.org](mailto:umap2022-wt at um.org) From papaleon at sch.gr Fri Dec 17 08:07:31 2021 From: papaleon at sch.gr (Papaleonidas Antonis) Date: Fri, 17 Dec 2021 15:07:31 +0200 Subject: Connectionists: 18th Artificial Intelligence Applications and Innovations International Conference Message-ID: <010401d7f347$0d724860$2856d920$@sch.gr> 18th International Conference on Artificial Intelligence Applications and Innovations 18th AIAI 2022, Hybrid @ Creta - Greece & Web 17 - 20 June, 2022, @ Web & Aldemar Knossos Royal, Crete, Greece https://ifipaiai.org/2022/ Dear colleagues We would like to invite you to submit your work at the 18th International Conference on Artificial Intelligence Applications and Innovations (AIAI2022 ) 18th International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022, is technically sponsored by IFIP Artificial Intelligence Applications WG12.5. It is going to be co-organized as a Joint event with 23rd Conference on Engineering Applications of Neural Networks, EANN 2022, which is technically sponsored by the INNS (International Neural Network Society). Hybrid event: the conference will be organized as a FULLY HYBRID event. Conference topics, CFPs, Submissions & Registration details can be found at: ifipaiai.org/2022/calls-for-papers/ ifipaiai.org/2022/paper-submission/ ifipaiai.org/2022/registration/ We are expecting Submissions on all topics related to Artificial and Computational Intelligence and their Applications. Detailed Guidelines on the Topics and the submission details can be found at the links above SPECIAL ISSUES - PROCEEDINGS: Selected papers will be published in 3 special issues of high quality international scientific Journals International Journal of Neural Systems, Impact factor 5.87 World Scientific https://www.worldscientific.com/worldscinet/ijns Neural Computing and Applications, Springer Impact Factor 5.61 https://link.springer.com/journal/521 The Springer Journal on AI and Ethics https://www.springer.com/journal/43681 PROCEEDINGS will be published SPRINGER IFIP AICT Series and they are INDEXED BY SCOPUS, DBLP, Google Scholar, ACM Digital Library, IO-Port, MAthSciNet, CPCI, Zentralblatt MATH and EI Engineering Index Papers submissions will be up to 12 pages long and not less than 6 pages. IMPORTANT DATES: Workshops & Special Sessions proposals deadline: 31st of December 2021 Paper Submission Deadline: 25th of February 2022 Notification of Acceptance: 26th of March 2022 Camera ready Submission: 22th of April 2022 Early / Authors Registration Deadline: 22th of April 2022 Conference: 17 - 20 of June 2022 *** Apologies for cross-posting *** Dr Papaleonidas Antonios Organizing - Publication & Publicity co-Chair of 18th AIAI 2022 Civil Engineering Department Democritus University of Thrace papaleon at civil.duth.gr papaleon at sch.gr -------------- next part -------------- An HTML attachment was scrubbed... URL: From georg.martius at tuebingen.mpg.de Fri Dec 17 09:41:16 2021 From: georg.martius at tuebingen.mpg.de (Georg Martius) Date: Fri, 17 Dec 2021 15:41:16 +0100 Subject: Connectionists: CFP: IMOL 2022 -- Intrinsically-Motivated Open-ended Learning Message-ID: Dear Colleagues, We are pleased to announce the ?Fifth International Workshop on Intrinsically-Motivated Open- ended Learning (IMOL2022)?, which will be held at Max Planck Institute for Intelligent Systems in Tu?bingen (Germany) on April 4-6th 2022. Following the four previous workshops, IMOL 2022 will further explore the advancements of intrinsically motivated open-ended lifelong learning. The workshop aims to be a highly interactive event with high-profile keynote presentations and the participation of an audience of about 60 people. It will foster close interaction among the participants with discussions, poster sessions, and collective round tables directed towards specific objectives. **Participating in IMOL2022** Participation in the workshop is free of charge but, given the specific nature of the meeting, is limited to a restricted number of people. Prospective attendees should submit either a brief statement of motivation or (preferably) an abstract to be presented as a poster or contributed talk. The submission should be made by Feb 4th 2022 over easychair following the instructions at https://2022.imol-conf.org/ Topics of interest involve open-ended lifelong learning in autonomous agents and robots, for example: - Autonomous robot open-ended learning - Architectures for open-ended learning - Multi-task reinforcement learning - Deep reinforcement learning - Intrinsic motivations - Curriculum learning - Goal self-generation - Open-ended development - Multiple task solution and parameterized skills - Neural/probabilistic representations and abstractions - Goal-based skill learning - Knowledge transfer and avoidance of catastrophic forgetting - Compositionality and chunking - Abstraction and hierarchies of goals and skills - Visual planning and problem solving - Mitigating risks of real-world deployment of open-ended learning systems **Important Dates:** Abstract submission: Feb 4th 2022 Conference dates: April 4-6th 2022 **REAL at IMOL2022 a robotics competition** IMOL2022 will also host a hands-on micro-workshop on how to participate in the REAL 2021 competition ("Robot open-Ended Autonomous Learning"). The competition, started in 2021 and ending in 2022, aims to develop a benchmark in the field of open-ended learning, and to form a community focused on comparing models able to face the several interesting challenges posed by open-ended learning. The competition involves a simulated robot manipulating objects that: (1) first acquires sensorimotor competence in a fully autonomous way (no reward function, pre-wired knowledge on objects and actions, etc.), on the basis of mechanisms such as free exploration, curiosity, intrinsic motivations, and self-generated goals; (2) then it is tested with some ?extrinsic goals? to measure the quality of the autonomously acquired knowledge. The competition is based on a fully open-source software kit that relies on a very fast 3D simulator (PyBullet) and includes a fully functioning and modifiable "baseline? robot architecture. The kit allows a handy development of your models on your computer before submitting them. The top 3 winning teams will receive prizes. Important dates of the competition: - 23/08/2021: competition started - 18/01/2022: hands-on presentation of the competition - 04/04/2022: IMOL hands-on micro-workshop - 24/06/2022: competition ends - 12-15/09/2022: presentation of winners at ICDL 2022 (with launch of REAL 2022) For further details, please refer to the competition website: https://eval.ai/web/challenges/challenge-page/1134/overview Best regards from the organizers of IMOL: Georg Martius Rania Rayyes Christian Gumbsch Vieri Giuliano Santucci Gianluca Baldassarre -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 195 bytes Desc: OpenPGP digital signature URL: From lmuller2 at uwo.ca Fri Dec 17 23:53:02 2021 From: lmuller2 at uwo.ca (Lyle Muller) Date: Sat, 18 Dec 2021 04:53:02 +0000 Subject: Connectionists: MSc/PhD and Postdoctoral positions in Computational Brain Science at Western University (London, Ontario) Message-ID: <78D278F1-0A44-438D-9AEC-918F1E5D33E6@uwo.ca> MSc/PhD and Postdoctoral positions in Computational Brain Science at Western University (London, Ontario) The Computational Brain Science Group at Western University (Ontario) is offering competitive funding for MSc / PhD students as well as postdocs. Our highly collaborative group is part of the Brain and Mind Institute with the core labs working on the analysis and modelling of neurophysiological, neuroimaging, and behavioural data. More information about the funding programs can be found here: https://www.uwo.ca/bmi/cbs/graduate_training/prospective_students.html https://www.uwo.ca/bmi/cbs/graduate_training/prospective_postdocs.html To apply, please contact the PIs with whom you are interested to work by January 10th, 2022, by sending a single PDF file entitled _.pdf containing: * a CV * a short research statement (max. 2 pages) outlining your research interest and how it fits with ongoing work in the targeted lab * the name and contact information of 2 academic references. Both our group and the University are committed to fostering diversity in the sciences. Applications from underrepresented groups are strongly encouraged, and any interested applicants can write PIs directly to discuss the research environment at Western. -- Lyle Muller http://mullerlab.ca -------------- next part -------------- An HTML attachment was scrubbed... URL: From l.s.smith at cs.stir.ac.uk Sat Dec 18 06:59:49 2021 From: l.s.smith at cs.stir.ac.uk (Prof Leslie Smith) Date: Sat, 18 Dec 2021 11:59:49 -0000 Subject: Connectionists: Request for info related to hardware for perceptrons Message-ID: <8c0d0b054ff6f30c543ca160c2190541.squirrel@mail.cs.stir.ac.uk> Dear all: I'm writing a paper on hardware for Neural networks, and I recollect that in the 1960's there was a discrete-transistor-sized adaptive resistor developed for perceptrons, possibly by Rosenblatt. I can't find any record of it, or anything in USPTO: can anyone supply me with a link or a paper on it? with much thanks (and apologies too: I can't currently get into my office to look at my old papers) --Leslie Smith -- Prof Leslie Smith (Emeritus) Computing Science & Mathematics, University of Stirling, Stirling FK9 4LA Scotland, UK Tel +44 1786 467435 Web: http://www.cs.stir.ac.uk/~lss Blog: http://lestheprof.com From david at irdta.eu Sat Dec 18 10:38:53 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sat, 18 Dec 2021 16:38:53 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Spring - DeepLearn 2022 Summer Message-ID: <2104102079.88597.1639841933291@webmail.strato.com> Dear all, DeepLearn, the International School on Deep Learning, is running since 2017 successfully. Please note the next editions of the program in 2022: https://irdta.eu/deeplearn/2022sp/ https://irdta.eu/deeplearn/2022su/ Best regards, DeepLearn organizing team -------------- next part -------------- An HTML attachment was scrubbed... URL: From nico.schuck at gmail.com Fri Dec 17 11:45:58 2021 From: nico.schuck at gmail.com (Nicolas Schuck) Date: Fri, 17 Dec 2021 17:45:58 +0100 Subject: Connectionists: Postdoctoral Position at Max Planck Institute in Berlin Message-ID: Dear colleagues, A postdoc position in my lab at the Max Planck Institute in Berlin is available as part of an ERC funded project investigating age-related changes in memory replay using fMRI. Applicants should submit a cover letter describing research interests (max. 2 pages), a CV and 2 representative publications. More information about the position can be found here: https://www.mpib-berlin.mpg.de/1393516/2021-12-14-neurocode-postdoctoral-researcher?c=219557 The deadline is Jan 31 2022. Please forward this email to anybody who might be interested. Of course, I'd be happy to have an informal chat about the position with potentially interested candidates. Thank you, -- Dr. Nicolas Schuck Max Planck Research Group Leader Max Planck Institute for Human Development, Berlin, Germany schucklab.gitlab.io -------------- next part -------------- An HTML attachment was scrubbed... URL: From M.Loog at tudelft.nl Sun Dec 19 05:17:33 2021 From: M.Loog at tudelft.nl (Marco Loog - EWI) Date: Sun, 19 Dec 2021 10:17:33 +0000 Subject: Connectionists: Machine Learning for Regional Climate, Assistant Professorship in Message-ID: <74efa9e666fd4bf39040d1e17b7b9262@tudelft.nl> Assistant Professorship in Machine Learning for Regional Climate Tenure track position at Delft University of Technology within the context of its new climate action program. See the vacancy text for details: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=5084&jobTitle=Assistant%20Professor%20in%20Machine%20Learning%20for%20Regional%20Climate%20 From Nantia.Makrynioti at cwi.nl Mon Dec 20 04:16:40 2021 From: Nantia.Makrynioti at cwi.nl (Nantia Makrynioti) Date: Mon, 20 Dec 2021 10:16:40 +0100 (CET) Subject: Connectionists: Call for Papers: DBML 2022 (ICDE Workshop) Message-ID: <1638585426.31531386.1639991800480.JavaMail.zimbra@cwi.nl> Call for Papers --------------------------------------------------------------------------------------- DBML International Workshop on Databases and Machine Learning in conjunction with ICDE 2022 https://www.wis.ewi.tudelft.nl/dbml2022 May 9 2022 - Virtual event About the workshop --------------------------------------------------------------------------------------- After the increased adoption of machine learning (ML) in various applications and disciplines, a synergy between the database (DB) systems and ML communities emerged. Steps involved in an ML pipeline, such as data preparation and cleaning, feature engineering and management of the ML lifecycle, can benefit from research conducted by the data management community. For example, the management of the ML lifecycle requires mechanisms for modeling, storing and querying ML artifacts. Moreover, in many use cases pipelines require a mixture of relational and linear algebra operators raising the question of whether a seamless integration between the two algebras is possible. In the opposite direction, ML techniques are explored in core components of database systems, e.g., query optimization, indexing and monitoring. Traditionally hard problems in databases, such as cardinality estimation, or problems with high human supervision like DB administration, might benefit more from learning algorithms than from rule-based or cost-based approaches. The workshop aims at bringing together researchers and practitioners in the intersection of DB and ML research, providing a forum for DB-inspired or ML-inspired approaches addressing challenges encountered in each of the two areas. In particular, we welcome new research topics combining the strengths of both fields. Call for papers --------------------------------------------------------------------------------------- Topics of particular interest in the workshop include, but are not limited to: * Data collection and preparation for ML applications * Declarative machine learning on databases, data warehouses or data lakes * Hybrid optimization techniques for databases and machine learning * Model-aware data discovery, cleaning, and transformation * Benchmarking ML-oriented data management systems (data augmentation, data cleaning, etc) * Data management during the life cycle of ML models * Novel data management systems for accelerating training and inference of ML models * DB-inspired techniques for modeling, storage and provenance of ML artifacts * Learned database design, configuration and tuning * Machine learning for query optimization * Applied machine learning/deep learning for data integration * ML-enabled data exploration and discovery in data lakes * ML functionality inside DBMS Submission: The workshop will accept both regular papers (8 pages) and short papers (4 pages - work in progress, vision/outrageous ideas). Submission Website: https://easychair.org/conferences/?conf=dbml22 Important Dates --------------------------------------------------------------------------------------- Paper submission deadline: Jan 14, 2022 Authors notification: Feb 22, 2022 Camera ready version: Mar 08, 2022 Workshop day: May 9, 2022 Workshop chairs --------------------------------------------------------------------------------------- Rihan Hai (TU Delft) Nantia Makrynioti (CWI) Ioana Manolescu (INRIA) From winfree at caltech.edu Mon Dec 20 03:55:45 2021 From: winfree at caltech.edu (Erik Winfree) Date: Mon, 20 Dec 2021 00:55:45 -0800 Subject: Connectionists: Request for info related to hardware for perceptrons In-Reply-To: <8c0d0b054ff6f30c543ca160c2190541.squirrel@mail.cs.stir.ac.uk> References: <8c0d0b054ff6f30c543ca160c2190541.squirrel@mail.cs.stir.ac.uk> Message-ID: <021B5A72-4861-45C7-8081-A381B7900053@caltech.edu> This New York Times article is quite the blast from the past: https://www.nytimes.com/1958/07/13/archives/electronic-brain-teaches-itself.html Not quite the serious discussion you?re looking for, but still. Ever-so-slightly more grounded: https://news.cornell.edu/stories/2019/09/professors-perceptron-paved-way-ai-60-years-too-soon My dad, Art Winfree, was one of those Cornell undergraduates helping him build the electronic perceptron machines. He told me in 2001 that: Spkg of antiquity, Nature 29 March reminisces over "bionics", as it was called around 1960 when it lured me (highschool senior) in to engineering and biology. First stint of real research was in Cornell Aeronautical Labs where Frank Rosenblatt, my mentor and idol, was building "Perceptrons". Main problem was the synapse: how to store cumulative experience? Tried capacitors, but they leaked overnight. Finally an electrochemical cell involving silver deposition, sorta like a battery in reverse, with cumulatively altered resistance, modified by Hebb rule. Then Carver Mead started along silicon lines and eventually came up with a way to store electrons a long time w/o leaking. Wikipedia describes the machine that perhaps you are referring to as the "Mark 1 Perceptron? and has a picture (https://en.wikipedia.org/wiki/Perceptron), but refers to Bishop (2006) for details (also see http://csis.pace.edu/~ctappert/srd2011/rosenblatt-contributions.htm). The Mark 1 is referred to in Rosenblatt?s 600-page ?Principles of Neurodynamics? (1961), and has a low-quality photo (https://apps.dtic.mil/sti/pdfs/AD0256582.pdf), but implementation details are sparse, or at least, I could not easily find them. There must be a better description somewhere. Best regards, Erik > On Dec 18, 2021, at 3:59 AM, Prof Leslie Smith wrote: > > Dear all: > > I'm writing a paper on hardware for Neural networks, and I recollect that > in the 1960's there was a discrete-transistor-sized adaptive resistor > developed for perceptrons, possibly by Rosenblatt. I can't find any record > of it, or anything in USPTO: can anyone supply me with a link or a paper > on it? > > with much thanks (and apologies too: I can't currently get into my office > to look at my old papers) > > --Leslie Smith > > -- > Prof Leslie Smith (Emeritus) > Computing Science & Mathematics, > University of Stirling, Stirling FK9 4LA > Scotland, UK > Tel +44 1786 467435 > Web: http://www.cs.stir.ac.uk/~lss > Blog: http://lestheprof.com > -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.herzallah at aston.ac.uk Mon Dec 20 05:26:16 2021 From: r.herzallah at aston.ac.uk (Randa Herzallah) Date: Mon, 20 Dec 2021 10:26:16 +0000 Subject: Connectionists: PhD studentship in Quantum control Message-ID: Dear Colleagues, Appreciate if you can distribute this to your network. Application deadline is 31st Jan 2022, but potential candidates are encouraged to apply as soon as possible. PhD studentship in quantum modelling and control at Aston University A generous funding for a PhD student in quantum systems is available in the Mathematics department at Aston University. Our department is part of Aston Institute of Urban Technology and the Environment ? ASTUTE. The project will explore new ways of using external signals to actively influence and manipulate the evolving state of quantum systems. More details about the project and how to submit your application can be found here https://rherzallah.github.io/quantum/ Kind regards, ____________________________________________ Dr Randa Herzallah Reader in Mathematics [https://outlook.office365.com/actions/ei?u=http%3A%2F%2Fstatic.aston.ac.uk%2Femails%2Fsigs%2Fautef-2019.jpg&d=2021-11-22T08%3A29%3A16.124Z] College of Engineering and Physical Sciences Birmingham, B4 7ET, UK 0121 204 3124 aston.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.jolivet at ucl.ac.uk Mon Dec 20 09:19:02 2021 From: r.jolivet at ucl.ac.uk (Jolivet, Renaud) Date: Mon, 20 Dec 2021 14:19:02 +0000 Subject: Connectionists: Master in Systems Biology at Maastricht University Message-ID: Dear Colleagues and Students, Come study Systems Biology (incl. Neurosciences) in our Master?s program at Maastricht University https://www.maastrichtuniversity.nl/education/master/systems-biology. This is a 2-year full time program taught exclusively in English. See the curriculum here https://www.maastrichtuniversity.nl/education/master/systems-biology/courses-curriculum, and admission and registration procedures here https://www.maastrichtuniversity.nl/education/master/systems-biology/admission-registration. Deadline for application for the program starting in September 2022 is 1 May 2022 for non-EU/EEA applicants and 1 June 2022 for EU/EEA applicants. Come work with us in the heart of Europe in a student town with an excellent quality of life. UM is the 6th best Young University in the world according to the Times Higher Ed 2020 Young Universities Ranking. Cheers, Renaud ? Prof. Renaud B. Jolivet Neural Engineering and Computation, Chair Maastricht University Organization for Computational Neurosciences, Board of Directors Initiative for Science in Europe, External Policy Advisor and Board Member Marie Curie Alumni Association, Vice-Chair of Policy +41798302129 (mobile) ?+31433881741 (office)? r.jolivet at maastrichtuniversity.nl twitter.com/RenaudJolivet linkedin.com/in/renaud-jolivet-63b5534 scholar.google.ch/citations?user=9Ozwv7EAAAAJ&hl=en -------------- next part -------------- An HTML attachment was scrubbed... URL: From barto at cs.umass.edu Mon Dec 20 11:01:38 2021 From: barto at cs.umass.edu (barto) Date: Mon, 20 Dec 2021 11:01:38 -0500 Subject: Connectionists: Request for info related to hardware for perceptrons In-Reply-To: <8c0d0b054ff6f30c543ca160c2190541.squirrel@mail.cs.stir.ac.uk> References: <8c0d0b054ff6f30c543ca160c2190541.squirrel@mail.cs.stir.ac.uk> Message-ID: <72EBB0B2-9F52-4256-985E-4F342C3827CE@cs.umass.edu> Dear Professor Smith, Perhaps you are thinking of Bernard Widrow?s memristor. Here is aWikipedia article about it: https://en.wikipedia.org/wiki/Memistor Sincerely, A. Barto > On Dec 18, 2021, at 6:59 AM, Prof Leslie Smith wrote: > > Dear all: > > I'm writing a paper on hardware for Neural networks, and I recollect that > in the 1960's there was a discrete-transistor-sized adaptive resistor > developed for perceptrons, possibly by Rosenblatt. I can't find any record > of it, or anything in USPTO: can anyone supply me with a link or a paper > on it? > > with much thanks (and apologies too: I can't currently get into my office > to look at my old papers) > > --Leslie Smith > > -- > Prof Leslie Smith (Emeritus) > Computing Science & Mathematics, > University of Stirling, Stirling FK9 4LA > Scotland, UK > Tel +44 1786 467435 > Web: http://www.cs.stir.ac.uk/~lss > Blog: http://lestheprof.com > From Roderick.Murray-Smith at glasgow.ac.uk Mon Dec 20 12:03:11 2021 From: Roderick.Murray-Smith at glasgow.ac.uk (Roderick Murray-Smith) Date: Mon, 20 Dec 2021 17:03:11 +0000 Subject: Connectionists: academic vacancies in Machine learning at the School of Computing Science at the University of Glasgow Message-ID: please note that new academic posts in Glasgow are now live, with a deadline of 12th January 2022 for applications https://www.jobs.ac.uk/job/CKW444/lecturer-senior-lecturer-reader-in-machine-learning Applications for the post are welcome in the general area of Machine Learning, which complement existing strengths in the Information, Data and Analysis (IDA) Section of the School of Computing Science. This includes topics such as Machine Learning Algorithms, Machine Learning in Science, Causal Machine Learning/Inference, Deep Learning & Neural Models, Active and Reinforcement Learning, Multitask and Transfer Learning, Machine Learning for Computer Vision, Machine Learning for Search/Recommendation systems, Online Learning, Interpretable & Explainable Machine Learning, Responsible Machine Learning (incl. fairness and trustworthiness in ML) and Machine Learning for Healthcare Technologies (incl. Machine Learning for Computational Biology, Metabolomics and Bioinformatics). The postholder will develop, lead and sustain research of international standard in Computing Science; contribute to teaching, assessment, project supervision and curriculum design at undergraduate and postgraduate levels; and participate in School management and organisation. For appointment at Reader you will have an outstanding track record of national and international distinction and leadership in research, including publications, income, and awards, bringing external recognition and distinction to yourself and the University. This position is equivalent to US tenure track Assistant or Associate Professor. For further information please visit https://www.flipsnack.com/uofgrecruitment/lslr-machine-learning-flipbook/full-view.html Please apply online at: https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=071767 Closing date: 12 January 2022 Professor Roderick Murray-Smith Head of Section, Information, Data and Analysis Section, Inference, Dynamics and Interaction Research Group School of Computing Science University of Glasgow Phone: +44 141 330 4984 Web: http://www.dcs.gla.ac.uk/~rod An t-Ollamh Ruairidh Murray-Smith Ceannard Roinne, Roinn Fiosrachaidh, D?ta agus Anailis Buidheann Rannsachaidh air Oidheam, Dinimigeachd agus Eadar-obrachadh Sgoil Saidheans na Coimpiutaireachd Oilthigh Ghlaschu -------------- next part -------------- An HTML attachment was scrubbed... URL: From eneftci at uci.edu Tue Dec 21 02:36:30 2021 From: eneftci at uci.edu (Emre Neftci) Date: Tue, 21 Dec 2021 08:36:30 +0100 Subject: Connectionists: Call for 2022 Telluride Neuromorphic Cognition Engineering Workshop Topic Area Proposals Message-ID: <8d55b780-51f5-46e5-9b98-6abbf5b52778@www.fastmail.com> The Telluride Neuromorphic 2022 Workshop Organizers are soliciting topic area proposals for the 2022 Telluride Neuromorphic Cognition Engineering Workshop (http://tellurideneuromorphic.org/) which will run from June 26 to July 16 2022. Details of the call can be found here: https://docs.google.com/document/d/16m7iRLUESgwyM1Qzk8m40Y-hkip38W-dv1Vqrlu-cMM/view Important upcoming dates: - Jan 07. 2022: Proposer's Day (5PM CET/9am USA MT). We will answer questions from prospective proposers about the topic area organization. - Jan 16. 2022: Deadline for Topic Area Proposals. Emre Neftci on behalf of The 2022 Telluride Organizing Team -- Prof. Dr. Emre Neftci Head of Peter Gr?nberg Institute 15 - Neuromorphic Software Ecosystems Forschungszentrum J?lich www.fz-juelich.de/pgi/PGI-15 From ioannakoroni at csd.auth.gr Tue Dec 21 04:12:42 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 21 Dec 2021 11:12:42 +0200 Subject: Connectionists: =?utf-8?q?AIDA_Course_on__=22Deep_Learning_for_Th?= =?utf-8?q?ree-dimensional_=283D=29_Humans=E2=80=9D?= Message-ID: <05fa01d7f64a$e9a0a0b0$bce1e210$@csd.auth.gr> Online Course on "Deep Learning for Three-dimensional (3D) Humans? We will organize a short course on ?Deep Learning for Three-dimensional (3D) Humans? offered through the International Artificial Intelligence Doctoral Academy (AIDA). The purpose of this course is to overview the foundations and the current state of the art in deep learning techniques for 3D human shape analysis. WHEN: Monday 17th January 2022 from 09:00 to 17.00 CET WHERE: Online HOW TO REGISTER: https://www.i-aida.org/course/deep-learning-for-three-dimensional-3d-humans/ -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From T.Nowotny at sussex.ac.uk Tue Dec 21 05:56:59 2021 From: T.Nowotny at sussex.ac.uk (Thomas Nowotny) Date: Tue, 21 Dec 2021 10:56:59 +0000 Subject: Connectionists: Six studentships in biomimetic embodied AI Message-ID: Dear Connectionists, We are offering 6 PhD studentships in our unique be.AI doctoral training centre in biomimetic embodied AI (http://www.sussex.ac.uk/ccnr/be_ai) at the University of Sussex in Brighton. Deadline: 23 February 2022 Apply online: https://www.sussex.ac.uk/study/phd/apply Full details at https://www.sussex.ac.uk/study/fees-funding/phd-funding/view/1403-Leverhulme-Doctoral-Scholarship-Programme:-be.AI---biomimetic-embodied-Artificial-Intelligence and below. Kind regards & Merry Christmas, Thomas -- Prof. Thomas Nowotny Head of AI Research Group CCNR, Sussex Neuroscience Phone: +44-1273-678593 Engineering and Informatics, Fax: +44-1273-877873 University of Sussex, Falmer, Brighton BN1 9QJ sussex.ac.uk/informatics/tnowotny I support the University of Sussex Community Pledge, as I continue to help those around me during the pandemic. Small acts of collaboration, kindness and integrity can make a big difference. www.sussex.ac.uk/community-pledge PhD Studentships in be.AI - University of Sussex?s Leverhulme Doctoral Scholarship Programme in Biomimetic Embodied AI The University of Sussex invites applications for PhD studentships within the be.AI Leverhulme Doctoral Scholarship Programme (www.sussex.ac.uk/ccnr/be_ai) which brings together researchers from the humanities, life sciences and computing to pursue artificial intelligence (AI) in its original definition of understanding natural intelligence by emulating it in artificial systems. In our unique interdisciplinary centre, we advance the understanding of how the interaction between brain, body and environment gives rise to intelligence and how this insight can be used to build novel artificial intelligence. As a be.AI Scholar you will: * Be funded for 3.5 years with a tax free living allowance at the standard Research Council rate ? currently ?15,009 per year? and normally UK fees (there are options for international fees for outstanding candidates) * Be eligible for generous financial support of up to ?4,000 per year for training and research expenses, such as conference trips and experimental costs * Be eligible to apply for one of three 12 month postdoctoral research fellowships, available only to completing Leverhulme be.AI scholars * Benefit from supervision by world-leading researchers in many different aspects of AI * Benefit from taught courses in topics, such as ethics and data science. We are now accepting applications for the second intake ? 6 studentships to start in September 2022. You will be registered within one of the participating schools (Life Sciences, Engineering and Informatics, Psychology, Philosophy, Media Film & Music) but will be encouraged to perform cross-disciplinary research with academics across Schools. In be.AI, you will work in a community of like-minded students and researchers supported by your own research seminars, invited lectures by world leading speakers, as well as student-led conferences and cohort building events. -------------- next part -------------- An HTML attachment was scrubbed... URL: From cognitivium at sciencebeam.com Wed Dec 22 04:44:13 2021 From: cognitivium at sciencebeam.com (Mary) Date: Wed, 22 Dec 2021 13:14:13 +0330 Subject: Connectionists: Hands-on workshop-New Year Festival 2022 Message-ID: <202112220944.1BM9iFS5043609@scs-mx-04.ANDREW.cmu.edu> Dear Researchers, On behalf of the ScienceBeam company, we are delighted to announce that on the occasion of the new Year 2022, we would like to invite you to join us for the New Year Festival 2022. This festival includes a 3-day meeting and gathering with the international clinicians and researchers in Istanbul, Turkey, as well as the End-year big sales. The participants will take part in the hands-on Neurofeedback, QEEG, and tDCS workshop at a considerably lower registration rate, as in the new year gift. Due to the COVID-19 safety guidelines and considering that we emphasize on our workshops to be completely practical, the workshop will be held as in a semi-private workshop with a limited capacity. Topics to be covered in the QEEG Workshop: ? Basics of EEG signals and brain mapping ? EEG recording using the eWave system ? Introduction to the Neuroguide software ? EEG montages, different databases, asymmetry, coherence, absolute and relative powers Topics to be covered in the Neurofeedback Workshop: ? Introduction to the Feedback and brainwaves ? A practical guide to Neurofeedback therapy using the eWave system ? Diagnosis of mental disorders based on changes in the brain waves ? Assessment of treatment protocols, such as ADHD, depression, anxiety, etc? Topics to be covered in the tES Workshop: ? Introduction to the intracranial stimulations (TDCS, TACS, TRNS, TPCS) ? Applications of xCS in disorders, cognitive function, and cognitive rehabilitation ? Hands-on session with the eStim device This comprehensive workshop provides not only a broad and up-to-date exposure to the current state of QEEG, Neurofeedback, and tDCS methods, but also provides an opportunity to do Neurofeedback treatment as well as QEEG recording and analysis during hands-on sessions. All the attendees who have little or broad experience in QEEG and Neurofeedback will find this meeting a comprehensive and engaging workshop. We are delighted to invite you to join us for this fantastic meeting. This New Year Festival 2022 is a great opportunity for any researcher and clinician interested in the above-mentioned techniques, or anyone who?d be interested in adding these techniques to their research center or clinic. Special opportunities are waiting for you. So, even if you are not in Istanbul, do not miss this extraordinary opportunity and book your flight promptly. We are excited to see you! For more information regarding the workshop schedule and registration please visit the link below: https://sciencebeam.com/neurofeedback-and-qeeg-workshop-3/ Please click on the link below to see the workshop schedule: https://sciencebeam.com/wp-content/uploads/2021/12/Program-Schedule.pdf Feel free to share the flyer among interested people. Please bear in mind that the registration deadline is January 8th and limited seats are available. If you have any questions regarding the workshop, do not hesitate to contact us (workshop at sciencebeam.com , or WhatsApp: 00905356498587). We hope to see you soon in Istanbul. ? ? ? Mary Reae Human Neuroscience Dept. Manager @ScienceBeam mary at sciencebeam.com www.sciencebeam.com? -------------- next part -------------- An HTML attachment was scrubbed... URL: From federico.becattini at unifi.it Wed Dec 22 13:18:24 2021 From: federico.becattini at unifi.it (Federico Becattini) Date: Wed, 22 Dec 2021 19:18:24 +0100 Subject: Connectionists: [CFP] International Workshop on "Towards a Complete Analysis of People: From Face and Body to Clothes (T-CAP)" at ICIAP 2021 Message-ID: ******************************** Call for Papers ?Towards a Complete Analysis of People: From Face and Body to Clothes (T-CAP)? International Workshop at ICIAP 2021 https://sites.google.com/view/t-cap2021 ******************************** === SUBMISSIONS ARE OPEN!!! ==== Two types of paper are welcome:: ---------------------------- - Regular Papers - (novel contributions not published previously) ---------------------------- - Presentation Papers - (papers that have been already accepted for publication previously) ---------------------------- Apologies for multiple posting Please distribute this call to interested parties AIMS AND SCOPE =============== Human-centred data are extremely widespread and have been intensely investigated by researchers belonging to even very different fields, including Computer Vision, Machine Learning, and Artificial Intelligence. These research efforts are motivated by the several highly-informative aspects of humans that can be investigated, ranging from corporal elements (e.g. bodies, faces, hands, anthropometric measurements) to emotions and outward appearance (e.g. human garments and accessories). The huge amount and the extreme variety of this kind of data make the analysis and the use of learning approaches extremely challenging. In this context, several interesting problems can be addressed, such as the reliable detection and tracking of people, the estimation of the body pose, the development of new human-computer interaction paradigms based on expression and sentiment analysis. Furthermore, considering the crucial impact of human-centred technologies in many industrial application domains, the demand for accurate models able also to run on mobile and embedded solutions is constantly increasing. For instance, the analysis and manipulation of garments and accessories worn by people can play a crucial role in the fashion business. Also, the human pose estimation can be used to monitor and guarantee the safety between workers and industrial robotic arms. The goal of this workshop is to improve the communication between researchers and companies and to develop novel ideas that can shape the future of this area, in terms of motivations, methodologies, prospective trends, and potential industrial applications. Finally, a consideration about the privacy issues behind the acquisition and the use of human-centred data must be addressed for both the academia and companies. TOPICS ======= The topics of interest include but are not limited to: - Human Body - People Detection and Tracking - 2D/3D Human Pose Estimation - Action and Gesture Recognition - Anthropometric Measurements Estimation - Gait Analysis - Person Re-identification - 3D Body Reconstruction - Human Face - Facial Landmarks Detection - Head Pose Estimation - Facial Expression and Emotion Recognition - Outward Appearance - Garment-based Virtual Try-On - Human-centred Image and Video Synthesis - Generative Clothing - Human Clothing and Attribute Recognition - Fashion Image Manipulation - Outfit Recommendation - Human-centred Data - Novel Datasets with Human Data - Fairness and Biases in Human Analysis - Privacy-Preserving and Data Anonymization - First Person Vision for Human Behavior Understanding - Multimodal Data Fusion for Human Analysis - Computational Issues in Human Analysis Architectures - Biometrics - Face Recognition and Verification - Fingerprint and Iris Recognition - Morphing Attack Detection IMPORTANT DATES ================= - Paper Submission Deadline: March 24th, 2022 - Decision to Authors: April 15th, 2022 - Camera ready papers due: April 22nd, 2021 - Workshop date: TBA SUBMISSION GUIDELINES ====================== All the papers should be submitted at: https://cmt3.research.microsoft.com/TCAP2021. The maximum number of pages is 10 + 2 pages for references. While preparing their contributions, authors must follow guidelines and technical instructions provided by Springer that can be found at: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines . At the time of submission, authors must indicate the type of the paper: - Regular papers: will be peer-reviewed following the same policy of the main conference (double-blind policy), and will be published in the proceedings. These are meant to present novel contributions not published previously (submitted papers should not have been published, accepted or under review elsewhere). - Presentation papers: are meant for papers that have been already accepted for publication previously, preferably in the last year in some major conferences or journals. These papers will undergo a soft-reviewing process from the chairs to assess the suitability for the workshop topics. These will not appear in the proceedings. The inclusion of both the above paper categories is meant to encourage dissemination and discussion of recent findings related to the workshop topics. Each accepted paper must be covered by at least one author registered. Registration can be either for the full event (5 days) at a regular rate or just for workshops and tutorials (2 days). WORKSHOP MODALITY ==================== The workshop will be held in conjunction with the International Conference on Image Analysis and Processing (ICIAP 2021). Both virtual and in presence participation will be allowed. ORGANIZING COMMITTEE ====================== - Prof. Mohamed Daoudi, IMT Lille Douai, France - Prof. Roberto Vezzani, University of Modena and Reggio Emilia, Italy - Guido Borghi, University of Bologna, Italy - Claudio Ferrari, University of Parma, Italy - Marcella Cornia, University of Modena and Reggio Emilia, Italy - Federico Becattini, University of Florence, Italy - Andrea Pilzer, Aalto University, Finland -- Federico Becattini, Ph.D. Universit? di Firenze - MICC Tel.: +39 055 275 1394 https://www.micc.unifi.it/people/federico-becattini/ https://fedebecat.github.io/ federico.becattini at unifi.it -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Tue Dec 21 06:56:35 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 21 Dec 2021 13:56:35 +0200 Subject: Connectionists: =?utf-8?q?More_information_about_the_Free_on-line?= =?utf-8?q?_AIDA_Course_on_=22Deep_Learning_for_Three-dimensional_?= =?utf-8?b?KDNEKSBIdW1hbnPigJ0uIGh0dHBzOi8vc2l0ZXMuZ29vZ2xlLmNvbS92?= =?utf-8?q?iew/dl43dhuman?= Message-ID: <084001d7f661$ce036ab0$6a0a4010$@csd.auth.gr> IMT Nord Europe & University of Lille will organize a free online short course on ?Deep Learning for Three-dimensional (3D) Humans? offered through the International Artificial Intelligence Doctoral Academy (AIDA). The purpose of this course is to overview the foundations and the current state of the art in deep learning techniques for 3D human shape analysis. The success of deep learning in computer vision and image analysis, speech recognition, and natural language processing has driven the recent interest in developing similar models for 3D geometric data. However, it is less obvious how using convolutional neural networks (CNNs) architectures can be adapted to 3D data, given in the form of point clouds or meshes, where a regular structure is not directly available. The purpose of this course is to overview the foundations and the current state of the art in deep learning techniques for 3D shape analysis. This short course will cover the following topics: ? Fundamentals of differential geometry of surfaces. ? Classical methods for 3D shape analysis. ? Deep learning for 3D data: basic concepts of deep learning; extending CNN to 3D data; ? Generative methods for 3D data, autoencoders and GAN methods for 3D data. The targeted applications will be in 3D face and body shape analysis. LECTURER: - Mohamed Daoudi, mohamed.daoudi at imt-nord-europe.fr - Juan-Carlos Alvarez-Paiva - Naima Otberdout - Emery Pierson ORGANIZER: IMT Nord Europe & University of Lille REGISTRATION: Free of charge. WHEN: Monday 17th January 2022 from 09:00 to 17.00 CET WHERE: Online HOW TO REGISTER: If you are an AIDA Student* already, please Step (a) register in the course by filling the following form https://forms.gle/NW6sW4DacqsTm5XeA AND Step (b) enroll in the same course in the AIDA system ( https://www.i-aida.org/course/deep-learning-for-three-dimensional-3d-humans/), so that this course enter your AIDA Course Attendance Certificate. If you are not an AIDA Student do only step (a). *AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the 67 AIDA Members listed in this page: https://www.i-aida.org/about/members/) Prof. M. Daoudi IMT Nord Europe" ?????????????????? Mohamed Daoudi Professor IMT Lille Douai CRISTAL (UMR CNRS 9189), (Centre de recherche en informatique, signal et automatique de Lille) Adresse : IMT Lille Douai, Rue Guglielmo Marconi, 59650 Villeneuve-d?Ascq Page personnelle : http://pagesperso.telecom-lille.fr/daoudi/, http://www.cristal.univ-lille.fr/~daoudi E-mail : mohamed.daoudi at imt-lille-douai.fr Associate Editor Image and Vision Computing Associate Editor IEEE Transactions On Multimedia Associate Editor Journal of Imaging Associate Computer Vision and Image Understanding IAPR Fellow -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From boris.gutkin at ens.fr Wed Dec 22 09:54:52 2021 From: boris.gutkin at ens.fr (boris gutkin) Date: Wed, 22 Dec 2021 15:54:52 +0100 Subject: Connectionists: Postdoctoral Fellow in the Theoretical Neuroscience at the Theoretical Neuroscience Group, Institute of Cognitive Neuroscience, HSE University Moscow, Russia References: <5594775E-3C59-4DB9-ABD8-8B0F1E20A650@ens.fr> Message-ID: Postdoctoral Fellow in the Theoretical Neuroscience HSE University Institute of Cognitive Neuroscience, Theoretical Neuroscience Group Moscow, Russia > > Theoretical Neuroscience Group (TNG), CDM, Institute for Cognitive Neuroscience, HSE in Moscow, Russia, invites applications for postdoctoral research positions in the field of theoretical and computational neuroscience. > > Research interests of the TNG at the Centre for Cognition and Decision Making are wide ranging, carried out in collaboration with the experimental labs at the Center. Current research topics include computational psychiatry, computational neuroeconomics, information processing in neurons and circuits, as well as role of oscillations in cognition. The candidate will have the opportunity to further define and expand the Group?s research program. > > > Requirements > > The general requirements for the postdoctoral fellowship positions are the following: > ? Candidates must hold a recent PhD in the quantitative fields which was awarded over the last 5 years or received before starting work at HSE in a relevant field by an internationally recognized university and has been assessed by external reviewers as having the potential to pursue research that is publishable in leading peer-reviewed journals; > ? Candidates should have a strong background in in quantitative disciplines: applied mathematics, physics, computer science or engineering. Knowledge of biology, neuroscience and ability to work with data and in an inter-disciplinary environment is highly desired. > ? Fluent English is an obligatory condition as research and other activities are conducted in English. Knowledge of Russian is not required; > > > The position involves: > ? working under the direct supervision of Boris Gutkin, Leading Scientist at the CCDM > ? participants are encouraged to pursue their own research along with working on the TNG research projects such as: > o computational neurobiology > o neural dynamics > o computational neuroeconomics > o computational psychiatry > ? writing research papers for international peer-reviewed journals in co-authorship with the members of CDM; > ? participation in the events of the TNG, CDM and the Institute for Cognitive Neuroscience and other contribution to the TNG/CMD development; > ? public presentations of candidate?s own research to the academic community; > ? some teaching is encouraged, though not required. > > > Conditions > > Appointments are made for one year. Postdoctoral fellows have an opportunity of renewal of the contract (no more than two times). > > HSE University offers postdoctoral fellows a competitive salary, the standard medical insurance plan, a working space equipped with a computer and free Internet access at the University. > > Candidates will be trained in model building, analysis and will be offered advanced training in neuroscience and cognitive psychology. Candidates will have an opportunity to develop independent research projects and collaborations under the direction of the group leading scientists. > > The TNG is a structural part of the HSE?s Centre for Cognition & Decision Making with ample collaboration opportunities within the Centre with other research groups, both within Russia and internationally. This new international group is tightly linked with the Group for Neural Theory at the Ecole Normale Superior in Paris, where research internships and visiting positions can be made available. > > > Application Process > > Applications must be submitted online. Please provide a CV, a statement of research interest and a recent research paper submitted via an online application form. At least two letters of recommendation should be sent directly to the International Faculty Recruitment Office at fellowship at hse.ru before the application deadline. Please note that direct applications to the hiring CDM may not be reviewed. > > Read more about the application process here . > > > The deadline for the applications is January 31, 2022. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From nagai.yukie at mail.u-tokyo.ac.jp Wed Dec 22 05:01:51 2021 From: nagai.yukie at mail.u-tokyo.ac.jp (nagai.yukie at mail.u-tokyo.ac.jp) Date: Wed, 22 Dec 2021 10:01:51 +0000 Subject: Connectionists: Assistant Professor / Postdoc Researcher in computational neuroscience and/or developmental robotics at the University of Tokyo Message-ID: Dear colleagues, The International Research Center for Neurointelligence (IRCN) at the University of Tokyo is looking for highly motivated full-time Assistant Professor / Postdoc researchers in the field of computational neuroscience and/or developmental robotics. The selected candidates will join Cognitive Developmental Robotics Laboratory head by Prof. Yukie Nagai and investigate the underlying mechanisms of human cognitive development and disorders by means of computational approaches. We design computational neural networks inspired by the human brain and examine what enables the networks to acquire human-like intelligence. Please send the required documents if you are interested in being considered. Assistant Professor / Postdoc Researcher at IRCN, the University of Tokyo https://ircn.jp/wp-content/uploads/2021/12/20211220_IRCN_Nagai_lab_2EN.pdf Cognitive Developmental Robotics Laboratory (Nagai Lab) http://developmental-robotics.jp ---------- 1. Job title / Number of positions Project Research Associate or Project Researcher (Postdoctoral Fellow) / One or two 2. Employment period Starting Date: Negotiable Contract duration: until March 31, 2022 3. Renewable The contract is renewable on a fiscal year basis (from April 1 to March 31; every year) according to research budget, research activity, and research achievements. Contract duration is until March 31, 2026. 4. Place of work International Research Center for Neurointelligence, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo, 113-0033 JAPAN 5. Description Successful applicants will work in the fields of computational neuroscience, cognitive developmental robotics, machine learning, and relevant topics. They will investigate the principle of human cognitive development and disorders by modeling computational neural networks inspired by the human brain and/or analyzing human cognitive behaviors. Please see the lab homepage (https://developmental-robotics.jp/en/) for more details. 6. Salary and benefits Salary: To be determined in accordance with the University of Tokyo Regulations Commuter allowance: JPY55,000 per month at maximum No retirement benefits or bonuses 7. Qualifications - PhD in engineering, computer science, cognitive science, neuroscience, or relevant fields - Communication skills in English - Programming skills - Experiences in computational neuroscience and/or cognitive developmental robotics are preferred 8. Application documents (1) Cover letter (A4 1 page) (2) Curriculum vita (3) Publication list (4) Research plan (A4 2-3 pages) (5) Name, affiliation, and email address of two references, one of which should be a previous employer or supervisor 9. Submission Please send the application documents (PDF) to yukie at ircn.jp 10. Application deadline / Selection process When the position is filled All applications will be screened, and only those qualified will be scheduled for an interview (on-site or online). 11. Inquiries Please contact Prof. Yukie Nagai at IRCN, the University of Tokyo yukie at ircn.jp ? Yukie Nagai, Ph.D. Project Professor, The University of Tokyo nagai.yukie at mail.u-tokyo.ac.jp | https://developmental-robotics.jp CREST Cognitive Mirroring: https://cognitive-mirroring.org CREST Cognitive Feeling: https://cognitive-feeling.jp From p.geurts at ulg.ac.be Wed Dec 22 04:57:47 2021 From: p.geurts at ulg.ac.be (Pierre Geurts) Date: Wed, 22 Dec 2021 10:57:47 +0100 Subject: Connectionists: =?utf-8?q?Open_academic_position_in_Brain_Inspire?= =?utf-8?q?d_Computing=2C_University_of_Li=C3=A8ge=2C_Belgium?= Message-ID: The University of Li?ge (ULi?ge) invites applications for a tenured or tenure-track full-time academic position in ?Brain Inspired Computing? in the Department of Electrical Engineering and Computer Science (Montefiore Institute) of the School of Engineering and Computer Science, to be filled ideally by September 1st, 2022. https://www.montefiore.uliege.be/cms/c_7790814/en/open-tenured-or-tenure-track-academic-position-in-brain-inspired-computing === The University of Li?ge === Founded in 1817, the University of Li?ge offers a complete range of university courses at undergraduate and postgraduate levels. It is divided into eleven faculties: Philosophy and Letters; Law, Political Science and Criminology; Sciences; Medicine; Applied Sciences; Veterinary Medicine; Psychology and Education; HEC Management School; Human and Social Sciences; Gembloux Agro-Bio Tech; and Architecture. === The Department of Electrical Engineering and Computer Science (Montefiore Institute) === At the School of engineering and computer science of the University of Li?ge, the Department of Electrical Engineering and Computer Science (EECS) offers several programs to undergraduate and graduate students. Since the end of the 19th century, it has developed a leading-edge tradition in teaching and research in a range of basic and applied topics in various areas of Information and Communication Technologies, Computer Science, Data Science, Electronics, Power Systems and Applied Mathematics, and it targets its efforts to contribute in application fields of societal importance, such as biomedical engineering, materials, energy systems, information systems, robotics, and transportation. The department has a long-standing tradition of international recruitment at the Faculty level, and organizes all its Master's programs in English. === Description of the position === The new faculty member will join the EECS department and develop theoretical and/or applied research on brain inspired computing, e.g. with a focus on one or several of the following topics (i) design of neuromorphic sensing and signal processing systems, such as event-based cameras and artificial skins, (ii) development of cognitive information processing methods, for example for high-level signal and image interpretation, (iii) neuromorphic design of embodied intelligence, e.g. for the development of adaptive and collaborative robots. He/she will also take part in the teaching activities at the graduate (Master) levels, in the fields of neuromorphic engineering, signal processing, and artificial intelligence organized by the EECS department. The selected candidate will be appointed either for a tenured position, or for a 4-year tenure track with a possibility to get tenure after 3 years. === Qualifications === ? A Dr or PhD degree, ? A high-level research experience in Brain Inspired Computing, ? A strong commitment in both fundamental and applied research, and a strong interest for teaching. === Application procedure === See here: https://www.montefiore.uliege.be/cms/c_7790814/en/open-tenured-or-tenure-track-academic-position-in-brain-inspired-computing From suashdeb at gmail.com Tue Dec 21 22:05:39 2021 From: suashdeb at gmail.com (Suash Deb) Date: Wed, 22 Dec 2021 08:35:39 +0530 Subject: Connectionists: Announcement of ISCMI22 (Toronto) Message-ID: Dear friends and esteemed colleagues, This is to announce 2022 9th ISCMI, to be held in Toronto next year http://iscmi.us/ Hope to receive your continued support for the same. Thanks in advance. I also take this opportunity of wishing you and your near and dear ones a very happy festive season and a joyful New Year With kind regards, Suash -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IICCI-NewYearCard2022.jpg Type: image/jpeg Size: 945379 bytes Desc: not available URL: From A.Soltoggio at lboro.ac.uk Wed Dec 22 07:52:24 2021 From: A.Soltoggio at lboro.ac.uk (Andrea Soltoggio) Date: Wed, 22 Dec 2021 12:52:24 +0000 Subject: Connectionists: Ph.D. positions in lifelong learning and neuromorphic AI/ML at Loughborough University Message-ID: Dear Connectionists, We would like to invite candidates to apply for funded Ph.D. positions in AI and ML at the Computer Science Department at Loughborough University. Topics of interest involve AI/ML areas such as lifelong learning, bio-inspired neural computation and spiking neural networks with a particular focus on applications in reinforcement learning, robotics, and edge-AI. Details. This new field of AI seeks to create machines that learn during a lifetime similarly to biological brains. This research continues and advances recent progress from the DARPA projects Lifelong Learning Machines (L2M) and Shared Experience Lifelong Learning (ShELL). The candidates will join a growing research group of Ph.D. students and postdocs working in the same area, and have access to the latest computational devices such as Nvidia A100 cards. Collaboration opportunities with world-leading AI laboratories will be encouraged and supported. Different projects will focus on aspects such as multi-agent neural reinforcement learning, neuromodulation, continual learning, low-power edge-computing, neuromorphic algorithms and implementations. Applications areas include autonomous vehicles and agents, advanced industrial systems, drones and other distributed robotic systems. Further additional links to our latest news and papers: https://www.azorobotics.com/News.aspx?newsID=12518 https://openreview.net/forum?id=BJge3TNKwH https://arxiv.org/abs/1703.10371 https://www.frontiersin.org/articles/10.3389/fncom.2021.666131/full https://ieeexplore.ieee.org/abstract/document/9534283 Loughborough University Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you?ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Graduate School, including tailored careers advice, to help you succeed in your research and future career. Entry requirements Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in computer science or a related subject. A relevant Master?s degree and/or experience in one or more of the following will be an advantage: artificial intelligence, neural networks, robotics. Funding information Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects within the School. Funding decisions will not be confirmed until early 2022. The studentship is for 3 years and provides a tax-free stipend of ?15,609 per annum for the duration of the studentship plus tuition fees at the UK rate. International (including EU) students may apply however the total value of the studentship will cover the International Tuition Fee Only. The position will be starting in October 2022 under the supervision of Dr. Andrea Soltoggio and Dr. Shirin Dora. If interested, please get in touch by emailing a.soltoggio at lboro.ac.uk or s.dora at lboro.ac.uk . Sincerely, Andrea Soltoggio and Shirin Dora -- Dr. Andrea Soltoggio (he/him or they/them) Senior Lecturer (Associate Professor) in Artificial Intelligence Department of Computer Science, School of Science & Intelligent Automation Centre https://www.intelligent-automation.org.uk/about-us/centre-staff & Centre for Information Management https://www.lboro.ac.uk/departments/sbe/cim/ Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Email: a.soltoggio at lboro.ac.uk Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From cgf at isep.ipp.pt Tue Dec 21 18:49:12 2021 From: cgf at isep.ipp.pt (Carlos) Date: Tue, 21 Dec 2021 23:49:12 +0000 Subject: Connectionists: CFP: Classification and Data Science in the Digital Age - IFCS 2022 Message-ID: Call for Papers IFCS 2022 Classification and Data Science in the Digital Age 17th Conference of the International Federation of Classification Societies 19th-23rd July 2022 ? Porto, Portugal Conference website: https://ifcs2022.fep.up.pt/ Write to us at: ifcs2022 at fep.up.pt We are proud to announce the keynote speakers that have already confirmed their participation to the IFCS 2022 Conference: -Genevera Allen (USA) -Charles Bouveyron (FR) -Dianne Cook (AUS) -Jo?o Gama (PT) -------------------------------------------- Publications -------------------------------------------- -Pre-conference Proceedings (6-8 page papers) in the Springer Series: "Studies in Classification, Data Analysis, and Knowledge Organization" -Post-conference Special Issues: -Advances in Data Analysis and Classification (ADAC) -Journal of Classification -Machine Learning -EURO Journal on Computational Optimization -------------------------------------------- Conference topics -------------------------------------------- -Big Data -Biplots -Clustering, Classification and Discrimination -Compositional Data Analysis -Computer Graphics and Visualization -Data Science -Data Streams -Databases and Data Management -Deep Learning -Dependence Modelling and Copulas -Dimension Reduction -Formal Concept Analysis -Functional Data Analysis -Generalized Linear Models -Image Analysis and Computer Vision -Information-theoretic Statistical Modelling and Model Selection -Knowledge Representation and Discovery -Machine Learning -Mathematical Foundations of Data Science -Matrix Factorization -Meta-learning -Missing Data Handling -Model-based Clustering -Modelling -High-Dimensional and Complex Data -Natural Language Processing -Optimization in Classification and Clustering -Pattern Recognition -Robust Methods -Social Network Analysis -Spatial Data Analysis -Statistical and Econometric Methods -Statistical Learning and Data Mining -Symbolic Data Analysis -Text Mining -Time Series Analysis -Web Mining with Applications in -Archaeology -Astronomy -Biology -Business and Management -Economics -Education -Engineering -Finance -Geosciences -Industry -Linguistics -Marketing -Medicine and Health Care -Musicology -Psychology -Risk Management -Social Sciences -------------------------------------------- Important dates: -------------------------------------------- January 15th, 2022 - Submission of full papers March 1st, 2022 - Notification to authors March 15th, 2022 - Submission of revised papers March 31st, 2022 - Deadline Submission of Single Abstracts April 14th, 2022 - Notification to Single Abstract Authors April 30th, 2022- Early registration deadline June 15th, 2022- Standard registration deadline after June 15th, 2022 - Late registration deadline We look forward to meeting you in Porto in July 2022 ! Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. Ant?nio Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From benabbessarra at gmail.com Thu Dec 23 04:35:28 2021 From: benabbessarra at gmail.com (=?UTF-8?Q?Sarra_Ben_Abb=C3=A8s?=) Date: Thu, 23 Dec 2021 10:35:28 +0100 Subject: Connectionists: 3rd International workshop on Deep Learning meets Ontologies and Natural Language Processing @ESWC 2022 Message-ID: Dear colleagues and researchers, Please consider to contribute to the 3rd edition of the international workshop "*Deep Learning meets Ontologies and Natural Language Processing*" which will be held online or in Hersonissos, Greece May 29 - June 2, 2022. ======================================================================= The deadline for paper submissions is *March 18th, 2022* ======================================================================= *DeepOntoNLP-2022* 3rd International workshop on Deep Learning meets Ontologies and Natural Language Processing at ESWC 2022 https://2022.eswc-conferences.org/, Hersonissos, Greece May 29 - June 2, 2022 Workshop website: https://sites.google.com/view/deepontonlp2022/ ======================================================================= *Context* In recent years, deep learning has been applied successfully and achieved state-of-the-art performance in a variety of domains, such as image analysis. Despite this success, deep learning models remain hard to analyze data and understand what knowledge is represented in them, and how they generate decisions. Deep Learning (DL) meets Natural Language Processing (NLP) to solve human language problems for further applications, such as information extraction, machine translation, search, and summarization. Previous works have attested the positive impact of domain knowledge on data analysis and vice versa, for example pre-processing data, searching data, redundancy and inconsistency data, knowledge engineering, domain concepts, and relationships extraction, etc. Ontology is a structured knowledge representation that facilitates data access (data sharing and reuse) and assists the DL process as well. DL meets recent ontologies and tries to model data representations with many layers of non-linear transformations. The combination of DL, ontologies, and NLP might be beneficial for different tasks: - Deep Learning for Ontologies: ontology population, ontology extension, ontology learning, ontology alignment, and integration, - Ontologies for Deep Learning: semantic graph embeddings, latent semantic representation, hybrid embeddings (symbolic and semantic representations), - Deep Learning for NLP: summarization, translation, named entity recognition, question answering, document classification, etc. - NLP for Deep Learning: parsing (part-of-speech tagging), tokenization, sentence detection, dependency parsing, semantic role labeling, semantic dependency parsing, etc. *Objective* This workshop aims at demonstrating recent and future advances in semantic rich deep learning by using Semantic Web and NLP techniques which can reduce the semantic gap between the data, applications, machine learning, in order to obtain semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science, and academia to exchange ideas and discuss the results of ongoing research in natural language processing, structured knowledge, and deep learning approaches. ======================================================================= We invite the submission of original works that are related -- but are not limited to -- the topics below. Topics of interest: - Construction ontology embeddings - Ontology-based text classification - Learning ontology embeddings - Semantic role labeling - Ontology reasoning with Deep Neural Networks - Deep learning for ontological semantic annotations - Spatial and temporal ontology embeddings - Ontology alignment and matching based on deep learning models - Ontology learning from text using deep learning models - Unsupervised Learning - Text classification using deep models - Neural machine translation - Deep question answering - Deep text summarization - Deep speech recognition - and so on. Submission: The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts, and approaches. All submissions must be PDF documents written in English and formatted according to LNCS instructions for authors https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines . Papers are to be submitted through the workshop's EasyChair submission page: https://easychair.org/conferences/?conf=deepontonlp2022. We welcome the following types of contributions: - Full research papers (8-10 pages): Finished or consolidated R&D works, to be included in one of the Workshop topics - Short papers (4-6 pages): Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper, there, and at the conference. For further please refer to the ESWC 2022 page: https://2022.eswc-conferences.org/ Important dates: - Workshop paper submission due: March 18th, 2022 - Workshop paper notifications: April 15th, 2022 - Workshop paper camera-ready versions due: April 22th, 2022 - Workshop: 28th or the 29th of May, 2022 (Half-Day) All deadlines are 23:59 anywhere on earth (UTC-12). Publication: The best papers from this workshop may be included in the supplementary proceedings of ESWC 2022. ======================================================================= Workshop Chairs Sarra Ben Abb?s, Engie, France Rim Hantach, Engie, France Philippe Calvez, Engie, France Program Committee Nada Mimouni, CNAM, France Lynda Temal, Engie, France Davide Buscaldi, LIPN, Universit? Sorbonne Paris Nord, France Valentina Janev, Mihajlo Pupin Institute, Serbia Mohamed Hedi Karray, LGP-INP-ENIT, Universit? de Toulouse, France -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sat Dec 25 13:24:25 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sat, 25 Dec 2021 19:24:25 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Summer: early registration January 17 Message-ID: <1126563403.1281762.1640456665139@webmail.strato.com> ****************************************************************** 6th INTERNATIONAL GRAN CANARIA SCHOOL ON DEEP LEARNING DeepLearn 2022 Summer Las Palmas de Gran Canaria, Spain July 25-29, 2022 https://irdta.eu/deeplearn/2022su/ ***************** Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Early registration: January 17, 2022 ****************************************************************** SCOPE: DeepLearn 2022 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Bournemouth, and Guimar?es. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Instituci?n Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/index.php?option=com_k2&view=item&layout=item&id=360&Itemid=896 STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Wahid Bhimji (Lawrence Berkeley National Laboratory), Deep Learning on Supercomputers for Fundamental Science Joachim M. Buhmann (Swiss Federal Institute of Technology Zurich), Machine Learning -- A Paradigm Shift in Human Thought!? Kate Saenko (Boston University), Overcoming Dataset Bias in Deep Learning PROFESSORS AND COURSES: T?lay Adal? (University of Maryland Baltimore County), [intermediate] Data Fusion Using Matrix and Tensor Factorizations Pierre Baldi (University of California Irvine), [intermediate/advanced] Deep Learning: From Theory to Applications in the Natural Sciences Arindam Banerjee (University of Illinois Urbana-Champaign), [intermediate/advanced] Deep Generative and Dynamical Models Mikhail Belkin (University of California San Diego), [intermediate/advanced] Modern Machine Learning and Deep Learning through the Prism of Interpolation Dumitru Erhan (Google), [intermediate/advanced] Visual Self-supervised Learning and World Models Arthur Gretton (University College London), [intermediate/advanced] Probability Divergences and Generative Models Phillip Isola (Massachusetts Institute of Technology), [intermediate] Deep Generative Models Mohit Iyyer (University of Massachusetts Amherst), [intermediate/advanced] Natural Language Generation Irwin King (Chinese University of Hong Kong), [intermediate/advanced] Deep Learning on Graphs Vincent Lepetit (Paris Institute of Technology), [intermediate] Deep Learning and 3D Reasoning for 3D Scene Understanding Yan Liu (University of Southern California), [introductory/intermediate] Deep Learning for Time Series Dimitris N. Metaxas (Rutgers, The State University of New Jersey), [intermediate/advanced] Model-based, Explainable, Semisupervised and Unsupervised Machine Learning for Dynamic Analytics in Computer Vision and Medical Image Analysis Sean Meyn (University of Florida), [introductory/intermediate] Reinforcement Learning: Fundamentals, and Roadmaps for Successful Design Louis-Philippe Morency (Carnegie Mellon University), [intermediate/advanced] Multimodal Machine Learning Wojciech Samek (Fraunhofer Heinrich Hertz Institute), [introductory/intermediate] Explainable AI: Concepts, Methods and Applications Clara I. S?nchez (University of Amsterdam), [introductory/intermediate] Mechanisms for Trustworthy AI in Medical Image Analysis and Healthcare Bj?rn W. Schuller (Imperial College London), [introductory/intermediate] Deep Multimedia Processing Jonathon Shlens (Google), [introductory/intermediate] Introduction to Deep Learning in Computer Vision Johan Suykens (KU Leuven), [introductory/intermediate] Deep Learning, Neural Networks and Kernel Machines Csaba Szepesv?ri (University of Alberta), [intermediate/advanced] Tools and Techniques of Reinforcement Learning to Overcome Bellman's Curse of Dimensionality 1. Murat Tekalp (Ko? University), [intermediate/advanced] Deep Learning for Image/Video Restoration and Compression Alexandre Tkatchenko (University of Luxembourg), [introductory/intermediate] Machine Learning for Physics and Chemistry Li Xiong (Emory University), [introductory/intermediate] Differential Privacy and Certified Robustness for Deep Learning Ming Yuan (Columbia University), [intermediate/advanced] Low Rank Tensor Methods in High Dimensional Data Analysis OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by July 17, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 17, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 17, 2022. ORGANIZING COMMITTEE: Marisol Izquierdo (Las Palmas de Gran Canaria, local chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn/2022su/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://irdta.eu/deeplearn/2022su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria Universitat Rovira i Virgili Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From jiaxiangzhang at gmail.com Thu Dec 23 10:13:31 2021 From: jiaxiangzhang at gmail.com (Jiaxiang ZHANG) Date: Thu, 23 Dec 2021 15:13:31 +0000 Subject: Connectionists: Two Postdoc positions and one PhD studentship at Cardiff, UK Message-ID: [Apologize for cross-posting] Dear colleagues, We are seeking applicants for two postdoc positions (research associates) and one PhD studentship at Cardiff University Brain Research Imaging Centre (CUBRIC). The research associates will work on the neurocognitive mechanisms of human decision-making, integrating multimodal brain imaging (MEG, functional and diffusion MRI, and MRS) and computational modelling. The PhD will work on cohort data to understand information processing speed in humans. We encourage applicants from different disciplines, including cognitive neuroscience, imaging neuroscience, psychology, computer science, mathematics or physics. Job specs and application details are available online (see links below). For informal enquiries, please contact Dr Jiaxiang Zhang ( zhangj73 at cardiff.ac.uk) with your CV. A. Postdoc positions (Deadline: Jan 14, 2022) https://www.jobs.ac.uk/job/CLV361/research-associates-2-posts B. 3-year PhD studentship (Deadline: March 11, 2022) https://www.findaphd.com/phds/project/characterizing-inter-individual-differences-and-longitudinal-changes-in-information-processing-speed/?p139840 The successful candidates will be based at CUBRIC. CUBRIC houses a unique combination of state-of-the-art facilities and world-leading expertise, with 4 human MRI systems (2 x Siemens Prisma, 1 x Siemens Connectom, 1 x Siemens 7T), MEG, EEG, TMS, tDCS, clinical research units and testing labs. Further details of CUBRIC can be found on our web page ( http://sites.cardiff.ac.uk/cubric). Dr. Jiaxiang Zhang Cardiff University Brain Research Imaging Centre (CUBRIC) School of Psychology Cardiff University Maindy Road, Cardiff, CF24 4HQ http://ccbrain.org https://www.cardiff.ac.uk/people/view/518347-zhang-jiaxiang zhangj73 at cardiff.ac.uk +44 (0)29 2087 0471 -------------- next part -------------- An HTML attachment was scrubbed... URL: From fmschleif at googlemail.com Wed Dec 22 15:54:33 2021 From: fmschleif at googlemail.com (Frank-Michael Schleif) Date: Wed, 22 Dec 2021 21:54:33 +0100 Subject: Connectionists: =?utf-8?q?Open_position_for_AI_/_Semantic_/_NLP_/?= =?utf-8?q?_machine_learning_at_FHWS_in_W=C3=BCrzburg=2C_Germany?= Message-ID: We are creating a new center on artificial intelligence in Wuerzburg, Germany (CAIRO) with multiple open positions (right now we announced 1 professor position) https://www.fhws.de/service/stellenausschreibungen-der-fhws/online-stellenportal-fuer-professuren-und-lehrpersonal/ direct link: https://stellen.fhws.de/jobposting/56c82f2a26d49b9569b5da563ab29681edaa87c70?ref=homepage (english translation available - just scroll down) The positions are research professorships (German W2 level, maybe comparable to reader status or kind of assistant professor, well paid and tenured life long positions) and will establish a center for AI (CAIRO) in Wuerzburg - do research & attract projects - have some minimal administrative duties - have only 9 x 45 min teaching duties per week (9 SWS) during the terms - will be involved in the new created MSc program on Artificial Intelligence (MAI) Additional funding to establish a group is also available. This is an exciting moment and chance. The positions are located here in Wuerzburg and the curriculum will be (so far) in English only (it may be necessary to learn some German in the first years) . To be eligible it is mandatory to have 5 years working experience after MSc including at least 3 years of industrial experience (can be spread and industry related research (institutes) also count). The positions announced right now have the following topics: - 61.1.296 Semantic Data Processing and Cognitive Computing ? Artificial Cognitive Perception and Speech https://stellen.fhws.de/jobposting/56c82f2a26d49b9569b5da563ab29681edaa87c70?ref=homepage Please spread the word - would be happy to see many applications Frank -- ------------------------------------------------------- Prof. Dr. rer. nat. habil. Frank-Michael Schleif School of Computer Science University of Applied Sciences W?rzburg-Schweinfurt Sanderheinrichsleitenweg 20 Raum I-3.35 Tel.: +49(0) 931 351 18127 97074 W?rzburg Honorable Research Fellow The University of Birmingham Edgbaston Birmingham B15 2TT United Kingdom - email: frank-michael.schleif at fhws.de http://promos-science.blogspot.de/ https://www.techfak.uni-bielefeld.de/~fschleif/ ------------------------------------------------------- From malini.vinita.samarasinghe at ini.rub.de Thu Dec 23 08:17:30 2021 From: malini.vinita.samarasinghe at ini.rub.de (Vinita Samarasinghe) Date: Thu, 23 Dec 2021 14:17:30 +0100 Subject: Connectionists: Women in Memory Research - Workshop - March 7-9, 2022 Message-ID: <6ec46c4e-28ba-ad7c-70ee-0e557f7b16a1@ini.rub.de> In conjunction with International Women's Day the FOR 2812 is organising its first ?*Women in Memory Research*? event from *March 7-9, 2022.* The percentage of senior female university researchers in our field (in Germany) lies between 21% and 29%. Our goal is to increase these numbers! So come and learn what an academic career looks like at the Ruhr University Bochum and discover its advantages. You'll be introduced to the university and it's support structures, be able to participate in university wide programs, meet with female faculty, listen to some amazing scientific talks, present your research, and see what collaborative research looks like in the RUB memory research community. Sounds exciting? *Who can apply:*Female master?s students in their final year of study and recently graduated master?s students who are looking into an academic career in the area of memory research/neuroscience. Applicants must have excellent grades and be able to communicate in English. Selection of participants is competitive. We only have space for 12 participants! *How to apply:*Send your application including a one page letter of motivation, a current CV, master?s transcripts and a letter of recommendation from one of your professors. Your application should be sent, as a single PDF document, to Vinita Samarasinghe @for2812 at rub.deby January 23, 2022. If you need child care or any other support please note this in your application. *What to expect:*We will provide accommodation and cover travel costs of up to 500 Euro (some meals are included). The program will be offered in English; however, certain programs offered by the Ruhr University in conjunction with International Women's Day may be only available in German. You will be asked to present your current research in the form of a poster. *Contact:*Vinita Samarasinghe,for2812 at rub.de,?Tel: +49 234 32 27996, https://for2812.rub.de -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, NB 3/73 Postfachnummer 110 Universit?tstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email:samarasinghe at ini.rub.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From rpaudel142 at gmail.com Wed Dec 22 22:54:22 2021 From: rpaudel142 at gmail.com (Ramesh Paudel) Date: Wed, 22 Dec 2021 22:54:22 -0500 Subject: Connectionists: CFP : SaT-CPS 2022 - ACM Workshop on Secure and Trustworthy Cyber-Physical Systems Due on Dec 31 Message-ID: Dear Colleagues, *** Please accept our apologies if you receive multiple copies of this CFP *** Please consider submitting and/or forwarding to the appropriate groups/personnel the opportunity to submit to the ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (SaT-CPS 2022), which will be held in Baltimore-Washington DC area (or virtually) on April 26, 2022 in conjunction with the 12th ACM Conference on Data and Application Security and Privacy (CODASPY 2022). *** Paper submission deadline: December 30, 2021 *** *** Website: https://sites.google.com/view/sat-cps-2022/ *** SaT-CPS aims to represent a forum for researchers and practitioners from industry and academia interested in various areas of CPS security. SaT-CPS seeks novel submissions describing practical and theoretical solutions for cyber security challenges in CPS. Submissions can be from different application domains in CPS. Example topics of interest are given below, but are not limited to: Secure CPS architectures - Authentication mechanisms for CPS - Access control for CPS - Key management in CPS - Attack detection for CPS - Threat modeling for CPS - Forensics for CPS - Intrusion and anomaly detection for CPS - Trusted-computing in CPS - Energy-efficient and secure CPS - Availability, recovery, and auditing for CPS - Distributed secure solutions for CPS - Metrics and risk assessment approaches - Privacy and trust - Blockchain for CPS security - Data security and privacy for CPS - Digital twins for CPS - Wireless sensor network security - CPS/IoT malware analysis - CPS/IoT firmware analysis - Economics of security and privacy - Securing CPS in medical devices/systems - Securing CPS in civil engineering systems/devices - Physical layer security for CPS - Security on heterogeneous CPS - Securing CPS in automotive systems - Securing CPS in aerospace systems - Usability security and privacy of CPS - Secure protocol design in CPS - Vulnerability analysis of CPS - Anonymization in CPS - Embedded systems security - Formal security methods in CPS - Industrial control system security - Securing Internet-of-Things - Securing smart agriculture and related domains The workshop is planned for one day, April 26, 2022, on the last day of the conference. Instructions for Paper Authors All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal. All papers must be submitted electronically via the Easychair system: https://easychair.org/conferences/?conf=acmsatcps2022 Full-length papers Papers must be at most 10 pages in length in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template). Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM Digital Library. The presenter must register for the workshop before the deadline for author registration. Position papers and Work-in-progress papers We also invite short position papers and work-in-progress papers. Such papers can be of length up to 6 pages in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template), and must clearly state "Position Paper" or "Work in progress," as the case may be in the title section of the paper. These papers will be reviewed and accepted papers will be published in the conference proceedings. Important Dates Due date for full workshop submissions: December 30, 2021 Notification of acceptance to authors: February 10, 2022 Camera-ready of accepted papers: February 20, 2022 Workshop day: April 26, 2022 *- - - - - - - - - - -* *Ramesh Paudel, Ph.D.* Publicity and Web Co-Chair Research Scientist George Washington University Washington, DC. -------------- next part -------------- An HTML attachment was scrubbed... URL: From nergistmn at gmail.com Fri Dec 24 07:21:06 2021 From: nergistmn at gmail.com (Nergis Tomen) Date: Fri, 24 Dec 2021 13:21:06 +0100 Subject: Connectionists: Exciting open PhD positions in computational neuroscience and neuromorphic computer vision Message-ID: Dear Connectionists, 1) We have an exciting open PhD position at the intersection between computational neuroscience, deep learning and image processing at TU Delft, Netherlands. The position is part of a collaboration between the Computer Vision Lab and the Brinks Lab in Neurophysics, and the PhD candidate will be integrated into the newly founded Biomedical Intervention Optimization Lab (BIOLab) (https://www.tudelft.nl/ai/biolab). Candidates with a strong background in computational neuroscience and interest in deep learning and computer vision, as well as candidates with a strong background in machine learning and interest in biophysical neuron models are encouraged to apply. For more details and to apply online: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=5045 2) In addition, we have 2 open PhD positions in neuromorphic computer vision as part of the Biomorphic Intelligence Lab ( https://www.tudelft.nl/ai/biomorphic-intelligence-lab). The PhD candidate will perform research on biologically inspired computer vision pipelines using event-based cameras and spiking neural networks. For more details and to apply online: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=5055 https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=5059 >> TU Delft is an equal opportunity employer, all qualified candidates are strongly encouraged to apply. On behalf of the aforementioned labs, we especially welcome applications from historically underrepresented minorities in STEM fields. >> For more information, please contact Dr. Nergis Tomen (n.tomen at tudelft.nl ). Kind regards and happy holidays, Nergis. -------------- next part -------------- An HTML attachment was scrubbed... URL: From tt at cs.dal.ca Thu Dec 23 11:30:32 2021 From: tt at cs.dal.ca (Thomas Trappenberg) Date: Thu, 23 Dec 2021 12:30:32 -0400 Subject: Connectionists: PhD position in computer science with focus on computational neuroscience/psychology in Canada Message-ID: A funded PhD position is open to work with Dr Thomas Trappenberg (CS) and Dr Abraham Nunes (Psychiatry/CS) at Dalhousie University in Halifax, Canada, on Linking Neuronal Hyperexcitability to Circuit-Level Hippocampal Computations, Declarative Memory Impairments, and Lithium Response in Bipolar Disorder. Interested people are encouraged to write to Dr. Trappenberg at tt at cs.dal.ca for further inquiries. Some background in biophysical modelling is an asset. ------- Dr. Thomas Trappenberg Dalhousie University Faculty of Computer Science Halifax, NS Canada -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sat Dec 25 13:21:16 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sat, 25 Dec 2021 19:21:16 +0100 (CET) Subject: Connectionists: DeepLearn 2022 Spring: early registration January 14 Message-ID: <923791253.1281672.1640456476318@webmail.strato.com> ****************************************************************** 5th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2022 Spring Guimar?es, Portugal April 18-22, 2022 https://irdta.eu/deeplearn/2022sp/ ***************** Co-organized by: Algoritmi Center University of Minho, Guimar?es Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Early registration: January 14, 2022 ****************************************************************** SCOPE: DeepLearn 2022 Spring will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, and Bournemouth. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Spring is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Spring will take place in Guimar?es, in the north of Portugal, listed as UNESCO World Heritage Site and often referred to as the birthplace of the country. The venue will be: Hotel de Guimar?es Eduardo Manuel de Almeida 202 4810-440 Guimar?es http://www.hotel-guimaraes.com/ STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full in vivo online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Kate Smith-Miles (University of Melbourne), Stress-testing Algorithms via Instance Space Analysis Mihai Surdeanu (University of Arizona), Explainable Deep Learning for Natural Language Processing Zhongming Zhao (University of Texas, Houston), Deep Learning Approaches for Predicting Virus-Host Interactions and Drug Response PROFESSORS AND COURSES: Eneko Agirre (University of the Basque Country), [introductory/intermediate] Natural Language Processing in the Pretrained Language Model Era Mohammed Bennamoun (University of Western Australia), [intermediate/advanced] Deep Learning for 3D Vision Altan ?ak?r (Istanbul Technical University), [introductory] Introduction to Deep Learning with Apache Spark Rylan Conway (Amazon), [introductory/intermediate] Deep Learning for Digital Assistants Jifeng Dai (SenseTime Research), [intermediate] AutoML for Generic Computer Vision Tasks Jianfeng Gao (Microsoft Research), [introductory/intermediate] An Introduction to Conversational Information Retrieval Daniel George (JPMorgan Chase), [introductory] An Introductory Course on Machine Learning and Deep Learning with Mathematica/Wolfram Language Bohyung Han (Seoul National University), [introductory/intermediate] Robust Deep Learning Lina J. Karam (Lebanese American University), [introductory/intermediate] Deep Learning for Quality Robust Visual Recognition Xiaoming Liu (Michigan State University), [intermediate] Deep Learning for Trustworthy Biometrics Jennifer Ngadiuba (Fermi National Accelerator Laboratory), [intermediate] Ultra Low-latency and Low-area Machine Learning Inference at the Edge Lucila Ohno-Machado (University of California, San Diego), [introductory] Use of Predictive Models in Medicine and Biomedical Research Bhiksha Raj (Carnegie Mellon University), [introductory] Quantum Computing and Neural Networks Bart ter Haar Romenij (Eindhoven University of Technology), [intermediate] Deep Learning and Perceptual Grouping Kaushik Roy (Purdue University), [intermediate] Re-engineering Computing with Neuro-inspired Learning: Algorithms, Architecture, and Devices Walid Saad (Virginia Polytechnic Institute and State University), [intermediate/advanced] Machine Learning for Wireless Communications: Challenges and Opportunities Yvan Saeys (Ghent University), [introductory/intermediate] Interpreting Machine Learning Models Martin Schultz (J?lich Research Centre), [intermediate] Deep Learning for Air Quality, Weather and Climate Richa Singh (Indian Institute of Technology, Jodhpur), [introductory/intermediate] Trusted AI Sofia Vallecorsa (European Organization for Nuclear Research), [introductory/intermediate] Deep Generative Models for Science: Example Applications in Experimental Physics Michalis Vazirgiannis (?cole Polytechnique), [intermediate/advanced] Machine Learning with Graphs and Applications Guowei Wei (Michigan State University), [introductory/advanced] Integrating AI and Advanced Mathematics with Experimental Data for Forecasting Emerging SARS-CoV-2 Variants Xiaowei Xu (University of Arkansas, Little Rock), [intermediate/advanced] Deep Learning for NLP and Causal Inference Guoying Zhao (University of Oulu), [introductory/intermediate] Vision-based Emotion AI OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by April 10, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by April 10, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by April 10, 2022. ORGANIZING COMMITTEE: Dalila Dur?es (Braga, co-chair) Jos? Machado (Braga, co-chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) Paulo Novais (Braga, co-chair) David Silva (London, co-chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn/2022sp/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will get exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Accommodation suggestions are available at https://irdta.eu/deeplearn/2022sp/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Centro Algoritmi, University of Minho, Guimar?es School of Engineering, University of Minho Intelligent Systems Associate Laboratory, University of Minho Rovira i Virgili University Municipality of Guimar?es Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From gdrion at uliege.be Tue Dec 28 03:25:06 2021 From: gdrion at uliege.be (gdrion at uliege.be) Date: Tue, 28 Dec 2021 09:25:06 +0100 Subject: Connectionists: Academic position in Brain-inspired computing at the University of Liege, Belgium Message-ID: <52EA82DA-9B0C-47C8-98B4-D87550B35306@uliege.be> Dear all, the University of Li?ge, Belgium, is inviting applications for a tenure-track full-time academic position in ?Brain Inspired Computing", in the Department of Electrical Engineering and Computer Science (Montefiore Institute). Applicants are sought in one or more of the following areas: - design of neuromorphic sensing and signal processing systems, - development of cognitive information processing methods, - neuromorphic design of embodied intelligence. The deadline for sending applications is 15 February, 2022. The position and procedures are described in more details in https://www.montefiore.uliege.be/cms/c_7790814/en/open-tenured-or-tenure-track-academic-position-in-brain-inspired-computing Best, Guillaume Drion. -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcin at amu.edu.pl Tue Dec 28 13:31:20 2021 From: marcin at amu.edu.pl (Marcin Paprzycki) Date: Tue, 28 Dec 2021 19:31:20 +0100 Subject: Connectionists: FedCSIS 2021 publications -- available open access In-Reply-To: References: Message-ID: Dear Colleagues, Publications resulting from the FedCSIS 2021 conference (IEEE event; CORE rank B) are available open access online. 1. Proceedings are available as Volume 25 of Annals of Computer Science and Information Systems (they can be also found in the IEEE Digital Library); check them out at: https://annals-csis.org/Volume_25/ 2. Position and Communication Papers are available as Volume 26 of Annals of Computer Science and Information Systems; check them out at: https://annals-csis.org/Volume_26/ Enjoy reading them ;-) HAPPY NEW YEAR! Marcin Paprzycki -- Ta wiadomo?? zosta?a sprawdzona na obecno?? wirus?w przez oprogramowanie antywirusowe Avast. https://www.avast.com/antivirus From terese at imse-cnm.csic.es Tue Dec 28 16:46:34 2021 From: terese at imse-cnm.csic.es (Teresa Serrano) Date: Tue, 28 Dec 2021 22:46:34 +0100 Subject: Connectionists: postdoctoral position funded by Andalusian government Message-ID: <68c668ee-bc29-92f9-d682-2be83a60db1b@imse-cnm.csic.es> *The IMSE Neuromorphic Group is looking for post-doctoral researchers willing to join the group (*http://www2.imse-cnm.csic.es/neuromorphs/ ) *at the Instituto de Microelectronica of Seville* ** *RESEARCH TALENT RECRUITMENT PROGRAMME ?EMERGIA?* *SUMMARY OF THE CALL FOR APPLICATIONS*** ** Characteristics and purpose of the call The candidates should apply for an official call of the Andalusian Government. The purpose of the call is to facilitate the incorporation of top researchers with leadership skills, of any nationality into the universities and research institutions of Andalusia. Up to 60 grants will be awarded in order to hire experienced researchers for a maximum of 4 years. Applicants Requirements Candidates must hold a PhD degree obtained not earlier than 5 nor later than 12 years before the date of publication of this call in the Official Gazette (December 2021). Features of the aid and contracts A minimum gross salary of 35.278 EUR per year is established for the selected researchers. The candidate and the host institution are free to agree a higher remuneration. An additional contribution of up to 80,000 EUR for research costs will be granted. Applications We are looking for candidates interested in the design of spiking neural networks hardware and algorithms, with emphasis on vision or biomedical applications. The neuromorphic group at IMSE develops optical sensors and processors for high speed smart and cognitive processing of spike coded data. We do also research on spike based learning circuits and algorithms. Candidates become members of the IMSE neuromorphic group (http://www2.imse-cnm.csic.es/neuromorphs/ ), and will have the opportunity to participate in national and international projects in cooperation with top research institutions in Europe in areas such as micro- and nano-electronics fabrication, neuromorphic computing, emerging devices and advanced VLSI design. The research will be done in the facilities available at IMSE (http://www.imse-cnm.csic.es/) located at 15 minutes walking from the city center. IMSE is a mixed institute from the Spanish Research Council CSIC (www.csic.es ) and the University of Seville (www.us.es ). Therefore, successful candidates will have access to services and facilities of both institutions The documents needed for the full application are: 1.- Brief Curriculum Vitae (BCV) according to the sample available on the website of the SICA, or according to the one automatically generated from ?Curriculum vitae? application, available on the website of /Fundaci?n Espa?ola de Ciencia y Tecnolog?a/ (FECYT). BCV will have a maximum lenght of *4 pages.* 2.- A brief summary of the candidates research career, as well as his/her main research interest, highlighting up to 10 of his/her most relevant contributions detailed in the BCV, in a maximum length of *3 pages*. 3.- A research proposal of up to *15 pages*, including details of the research thatwould be developed at the host institution. The research proposal must include the following sections: a)Outline of the proposal b)Background to the research c)Objectives of the research d)Methodology and work plan e)Expected results and impact. Dissemination and operating plan. f)Justified and detailed budget. In the event of subcontracting third parties, state the amount, the companies? profiles and the research tasks the subcontracted parties would work on. The BCV, the summary of the research career and of the research proposal can be submitted in either English or Spanish and must be written in Noto Sans HK, Times New Roman or Arial font,11-points size; side margins of 2,5 cm; top and bottom margins of 1,5 cm; and minimum single spaced. Information about eligibility and evaluation criteria can not be amended after the call deadline. A careful reading of the call is recommended. Applicants must register in SICA (website:https://sica2.cica.es )in order to obtain an username and a password to be able to fill in and send the application form. Applications must be submitted via Internet using the electronic submission system of one of the following websites: https://sica2.cica.es http://www.juntadeandalucia.es/organismos/ transformacion economi c a industria conocimientoyuniversidad es .html http://www.juntadeandalucia.es/servicios/procedimientos.html Applications submission period Application submission deadline: From *January 3 to 31, 2022* *Evaluation organism* Applications will be evaluated by the Department of Evaluation and Accreditation (DEVA) of the Andalusian Knowledge Agency (/Agencia Andaluza del Conocimiento/) of Junta de Andaluc?a. Evaluation criteria The recruitment procedure is based on competitive tendering, according to thefollowing criteria: a) Curricular merits of the research candidate: up to 50 points. a.1) Scientific publications, patents, participations in RTD projects and contracts. Up to 35 points. a.2) Participation in RTD international activities. Up to 15 points b) Leadership potential of the research candidate. Up to 20 points. c) Quality and potential impact of the research proposal. Up to 30 points. The applications must reach a score of at least 80 points must be achieved once the previous stated threshold was reached. Procedure and deadlines Application submission: From *January 3 to 31, 2021* Amendment period: 10 working days after the deadline for submitting applications. Redress procedure after provisional awarding: 10 working days. Submission of incorporation agreement: period of not less than 10 days. Incorporation deadline Contract formalisation with beneficiary entities: 2 months. Incorporation of selected researchers: 9 months. Information Interested candidates. Please contact: bernabe at imse-cnm.csic.es C/ Am?rico Vespucio, 28 Parque Cient?fico y Tecnol?gico Cartuja 41092 Sevilla. SPAIN Ph.: +34 954 466 666 ? Fax: +34 954 466 600 -------------- next part -------------- An HTML attachment was scrubbed... URL: From rpaudel142 at gmail.com Tue Dec 28 11:45:31 2021 From: rpaudel142 at gmail.com (Ramesh Paudel) Date: Tue, 28 Dec 2021 11:45:31 -0500 Subject: Connectionists: CFP(Deadline Extended till Jan 7) : SaT-CPS 2022 - ACM Workshop on Secure and Trustworthy Cyber-Physical Systems Message-ID: Dear Colleagues, *** *This is a reminder that the CFP deadline is extended till Jan 07, 2022* *** Please consider submitting and/or forwarding to the appropriate groups/personnel the opportunity to submit to the ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (SaT-CPS 2022), which will be held in Baltimore-Washington DC area (or virtually) on April 26, 2022 in conjunction with the 12th ACM Conference on Data and Application Security and Privacy (CODASPY 2022). *** Paper submission deadline: *December 30, 2021 (Extended Jan 07, 2022)* *** *** Website: https://sites.google.com/view/sat-cps-2022/ *** SaT-CPS aims to represent a forum for researchers and practitioners from industry and academia interested in various areas of CPS security. SaT-CPS seeks novel submissions describing practical and theoretical solutions for cyber security challenges in CPS. Submissions can be from different application domains in CPS. Example topics of interest are given below, but are not limited to: Secure CPS architectures - Authentication mechanisms for CPS - Access control for CPS - Key management in CPS - Attack detection for CPS - Threat modeling for CPS - Forensics for CPS - Intrusion and anomaly detection for CPS - Trusted-computing in CPS - Energy-efficient and secure CPS - Availability, recovery, and auditing for CPS - Distributed secure solutions for CPS - Metrics and risk assessment approaches - Privacy and trust - Blockchain for CPS security - Data security and privacy for CPS - Digital twins for CPS - Wireless sensor network security - CPS/IoT malware analysis - CPS/IoT firmware analysis - Economics of security and privacy - Securing CPS in medical devices/systems - Securing CPS in civil engineering systems/devices - Physical layer security for CPS - Security on heterogeneous CPS - Securing CPS in automotive systems - Securing CPS in aerospace systems - Usability security and privacy of CPS - Secure protocol design in CPS - Vulnerability analysis of CPS - Anonymization in CPS - Embedded systems security - Formal security methods in CPS - Industrial control system security - Securing Internet-of-Things - Securing smart agriculture and related domains The workshop is planned for one day, April 26, 2022, on the last day of the conference. *Instructions for Paper Authors* All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal. All papers must be submitted electronically via the Easychair system: https://easychair.org/conferences/?conf=acmsatcps2022 Full-length papers Papers must be at most 10 pages in length in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template). Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM Digital Library. The presenter must register for the workshop before the deadline for author registration. *Position papers and Work-in-progress papers* We also invite short position papers and work-in-progress papers. Such papers can be of length up to 6 pages in double-column ACM format (as specified at https://www.acm.org/publications/proceedings-template), and must clearly state "Position Paper" or "Work in progress," as the case may be in the title section of the paper. These papers will be reviewed and accepted papers will be published in the conference proceedings. *Important Dates* Due date for full workshop submissions: *December 30, 2021 (Extended Jan 07, 2022)* Notification of acceptance to authors: February 10, 2022 Camera-ready of accepted papers: February 20, 2022 Workshop day: April 26, 2022 *- - - - - - - - - - -* *Ramesh Paudel, Ph.D.* Publicity and Web Co-Chair Research Scientist George Washington University Washington, DC. -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Wed Dec 29 10:36:14 2021 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Wed, 29 Dec 2021 15:36:14 +0000 Subject: Connectionists: NEURAL NETWORKS, Jan. 2022 Message-ID: Neural Networks - Volume 145, January 2022 https://www.journals.elsevier.com/neural-networks Editorial: Continual growth and a transition Kenji Doya, Taro Toyoizumi, DeLiang Wang Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, ... Xinbo Gao Generalized attention-weighted reinforcement learning Lennart Bramlage, Aurelio Cortese New effective approach to quasi synchronization of coupled heterogeneous complex networks Tianping Chen Meta-learning, social cognition and consciousness in brains and machines Angela Langdon, Matthew Botvinick, Hiroyuki Nakahara, Keiji Tanaka, ... Ryota Kanai Reinforcement learning and its connections with neuroscience and psychology Ajay Subramanian, Sharad Chitlangia, Veeky Baths Minimum spanning tree based graph neural network for emotion classification using EEG Hanjie Liu, Jinren Zhang, Qingshan Liu, Jinde Cao A complementary learning approach for expertise transference of human-optimized controllers Adolfo Perrusqu?a Interpolation consistency training for semi-supervised learning Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, ... David Lopez-Paz Learning policy scheduling for text augmentation Shuokai Li, Xiang Ao, Feiyang Pan, Qing He Cross-attention-map-based regularization for adversarial domain adaptation Jingwei Li, Huanjie Wang, Ke Wu, Chengbao Liu, Jie Tan Zenithal isotropic object counting by localization using adversarial training Javier Rodriguez-Vazquez, Adrian Alvarez-Fernandez, Martin Molina, Pascual Campoy Epistemic uncertainty quantification in deep learning classification by the Delta method Geir K. Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug, Morten Brun IC neuron: An efficient unit to construct neural networks Junyi An, Fengshan Liu, Furao Shen, Jian Zhao, ... Kepan Gao Detecting out-of-distribution samples via variational auto-encoder with reliable uncertainty estimation Xuming Ran, Mingkun Xu, Lingrui Mei, Qi Xu, Quanying Liu GuidedStyle: Attribute knowledge guided style manipulation for semantic face editing Xianxu Hou, Xiaokang Zhang, Hanbang Liang, Linlin Shen, ... Jun Wan Sparsity-control ternary weight networks Xiang Deng, Zhongfei Zhang Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction Ahmad Ali, Yanmin Zhu, Muhammad Zakarya Curriculum learning with Hindsight Experience Replay for sequential object manipulation tasks B. Manela, A. Biess Structure inference of networked system with the synergy of deep residual network and fully connected layer network Keke Huang, Shuo Li, Wenfeng Deng, Zhaofei Yu, Lei Ma Multi-level attention pooling for graph neural networks: Unifying graph representations with multiple localities Takeshi D. Itoh, Takatomi Kubo, Kazushi Ikeda Nostradamus: A novel event propagation prediction approach with spatio-temporal characteristics in non-Euclidean space Haizhou Du, Yan Zhou LGN-CNN: A biologically inspired CNN architecture Federico Bertoni, Giovanna Citti, Alessandro Sarti Approximation capabilities of neural networks on unbounded domains Ming-Xi Wang, Yang Qu Probabilistic generative modeling and reinforcement learning extract the intrinsic features of animal behavior Keita Mori, Naohiro Yamauchi, Haoyu Wang, Ken Sato, ... Yuichi Iino On the capacity of deep generative networks for approximating distributions Yunfei Yang, Zhen Li, Yang Wang Exponential synchronization of coupled neural networks under stochastic deception attacks Huihui Zhang, Lulu Li, Xiaodi Li Convergence analysis of AdaBound with relaxed bound functions for non-convex optimization Jinlan Liu, Jun Kong, Dongpo Xu, Miao Qi, Yinghua Lu Fractional-order discontinuous systems with indefinite LKFs: An application to fractional-order neural networks with time delays K. Udhayakumar, Fathalla A. Rihan, R. Rakkiyappan, Jinde Cao Event-based master-slave synchronization of complex-valued neural networks via pinning impulsive control Yuan Shen, Xinzhi Liu Enriching query semantics for code search with reinforcement learning Chaozheng Wang, Zhenhao Nong, Cuiyun Gao, Zongjie Li, ... Yang Liu Cardinality-constrained portfolio selection based on collaborative neurodynamic optimization Man-Fai Leung, Jun Wang FCL-Net: Towards accurate edge detection via Fine-scale Corrective Learning Wenjie Xuan, Shaoli Huang, Juhua Liu, Bo Du Cycle-consistent Adversarial Adaptation Network and its application to machine fault diagnosis Jinyang Jiao, Jing Lin, Ming Zhao, Kaixuan Liang, Chuancang Ding FOREX rate prediction improved by Elliott waves patterns based on neural networks Robert Jarusek, Eva Volna, Martin Kotyrba -------------- next part -------------- An HTML attachment was scrubbed... URL: From fabio.bellavia at unifi.it Wed Dec 29 04:43:33 2021 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Wed, 29 Dec 2021 10:43:33 +0100 Subject: Connectionists: [CfP] International workshop on "Fine Art Pattern Extraction and Recognition (FAPER 2022)" at ICIAP 2021 Message-ID: <09eadacc-bc86-19e1-50d3-373ed02597c9@unifi.it> ???????????????????? Call for Papers -- FAPER 2022 ??????????? ---===== Apologies for cross-postings =====--- ?????????? Please distribute this call to interested parties ________________________________________________________________________ ?International Workshop on Fine Art Pattern Extraction and Recognition ????????????????????????? F A P E R?? 2 0 2 2 ??????? in conjunction with the 21st International Conference on ?????????????? Image Analysis and Processing (ICIAP 2021) ???????????????????? Lecce, Italy, MAY 23-27, 2022 ??????????? >>> https://sites.google.com/view/faper2022 <<< ????????????? *** Submission deadline: March 1, 2022 *** -> Submission link: https://easychair.org/conferences/?conf=faper2022 <- ????????????? [[[ both virtual and in presence event ]]] ________________________________________________________________________ === Aim & Scope === Cultural heritage, especially fine arts, plays an invaluable role in the cultural, historical and economic growth of our societies. Fine arts are primarily developed for aesthetic purposes and are mainly expressed through painting, sculpture and architecture. In recent years, thanks to technological improvements and drastic cost reductions, a large-scale digitization effort has been made, which has led to an increasing availability of large digitized fine art collections. This availability, coupled with recent advances in pattern recognition and computer vision, has disclosed new opportunities, especially for researchers in these fields, to assist the art community with automatic tools to further analyze and understand fine arts. Among other benefits, a deeper understanding of fine arts has the potential to make them more accessible to a wider population, both in terms of fruition and creation, thus supporting the spread of culture. Following the success of the first edition, organized in conjunction with ICPR 2020, the aim of the workshop is to provide an international forum for those wishing to present advancements in the state-of-the-art, innovative research, ongoing projects, and academic and industrial reports on the application of visual pattern extraction and recognition for a better understanding and fruition of fine arts. The workshop solicits contributions from diverse areas such as pattern recognition, computer vision, artificial intelligence and image processing. === Topics === Topics of interest include, but are not limited to: - Application of machine learning and deep learning to cultural heritage and digital humanities - Computer vision and multimedia data processing for fine arts - Generative adversarial networks for artistic data - Augmented and virtual reality for cultural heritage - 3D reconstruction of historical artifacts - Point cloud segmentation and classification for cultural heritage - Historical document analysis - Content-based retrieval in the art domain - Speech, audio and music analysis from historical archives - Digitally enriched museum visits - Smart interactive experiences in cultural sites - Projects, products or prototypes for cultural heritage restoration, preservation and fruition - Visual question answering and artwork captioning - Art history and computer vision === Invited speaker === Eva Cetinic (Digital Visual Studies, University of Zurich, Switzerland) - "Beyond Similarity: From Stylistic Concepts to Computational Metrics" Dr. Eva Cetinic is currently working as a postdoctoral fellow at the Center for Digital Visual Studies at the University of Zurich. She previously worked as a postdoc in Digital Humanities and Machine Learning at the Department of Computer Science, Durham University, and as a postdoctoral researcher and professional associate at the Ru?er Bo?kovic Institute in Zagreb. She obtained her Ph.D. in Computer science from the Faculty of Electrical Engineering and Computing, University of Zagreb in 2019 with the thesis titled "Computational detection of stylistic properties of paintings based on high-level image feature analysis". Besides being generally interested in the interdisciplinary field of digital humanities, her specific interests focus on studying new research methodologies rooted in the intersection of artificial intelligence and art history. Particularly, she is interested in exploring deep learning techniques for computational image understanding and multi-modal reasoning in the context of visual art. === Workshop modality === The workshop will be held in a hybrid form, both virtual and in presence participation will be allowed. === Submission guidelines === Accepted manuscripts will be included in the ICIAP 2021 proceedings, which will be published by Springer as Lecture Notes in Computer Science series (LNCS). Authors of selected papers will be invited to extend and improve their contributions for a Special Issue on IET Image Processing. Please follow the guidelines provided by Springer when preparing your contribution. The maximum number of pages is 10 + 2 pages for references. Each contribution will be reviewed on the basis of originality, significance, clarity, soundness, relevance and technical content. Once accepted, the presence of at least one author at the event and the oral presentation of the paper are expected. Please submit your manuscript through EasyChair: https://easychair.org/conferences/?conf=faper2022 === Important Dates === - Workshop submission deadline: March 1st 2022 - Author notification: March 10th 2022 - Camera-ready submission and registration: March 15th 2022 - Finalized workshop program: TBA - Workshop day: TBA === Organizing committee === Gennaro Vessio (University of Bari, Italy) Giovanna Castellano (University of Bari, Italy) Fabio Bellavia (University of Palermo, Italy) Sinem Aslan (University of Venice, Italy | Ege University, Turkey) === Venue === The workshop will be hosted at Convitto Palmieri, which is located in Piazzetta di Giosue' Carducci, Lecce, Italy ____________________________________________________ ?Contacts: gennaro.vessio at uniba.it ?????????? giovanna.castellano at uniba.it ?????????? fabio.bellavia at unipa.it ?????????? sinem.aslan at unive.it ?Workshop: https://sites.google.com/view/faper2022 ICIAP2021: https://www.iciap2021.org/ From marius.pedersen at ntnu.no Wed Dec 29 06:22:17 2021 From: marius.pedersen at ntnu.no (Marius Pedersen) Date: Wed, 29 Dec 2021 11:22:17 +0000 Subject: Connectionists: Postdoctoral Fellow in Deep Learning-Based Image Quality Assessment Message-ID: We have an open 41 months Postdoctoral position in deep learning-based image quality assessment at Norwegian Colour and Visual Computing Laboratory (Colourlab) at the Norwegian university of Science and Technology (NTNU). The post doc position is part of the research project "Quality and Content: understanding the influence of content on subjective and objective image quality assessment". The project aims to advance the understanding of image quality and develop more precise and better performing image quality metrics based on improved understanding on how content influences image quality. The Postdoctoral position will focus on developing more precise and better performing image quality metrics using deep learning and understanding on how content influences image quality. Deadline: 15th of January 2022 More information and the process for applying is found at https://www.jobbnorge.no/en/available-jobs/job/217799/postdoctoral-fellow-in-deep-learning-based-image-quality-assessment Best regards Marius Pedersen Professor of Colour Imaging Director of the Norwegian Colour and Visual Computing Laboratory www.colourlab.no Department of Computer Science NTNU marius.pedersen at ntnu.no - (+47) 93 63 43 85 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Francesco.Rea at iit.it Wed Dec 29 10:17:50 2021 From: Francesco.Rea at iit.it (Francesco Rea) Date: Wed, 29 Dec 2021 15:17:50 +0000 Subject: Connectionists: [jobs] Post-doc Functional Memory Network in collaborative AI for context awareness and action planning in robotics @ Italian Institute of Technology (IIT) Message-ID: <5d11237d34e548a2a241ac62033197f9@iit.it> Post-doc Functional Memory Network in collaborative AI for context awareness and action planning in robotics At IIT we work enthusiastically to develop human-centered Science and Technology to tackle some of the most pressing societal challenges of our times and transfer these technologies to the production system and society. Our Genoa headquarter is strictly inter-connected with our 11 centers around Italy and two outer-stations based in the US for a truly interdisciplinary experience. The CONTACT Research Line is coordinated by Alessandra Sciutti, who has extensive experience in Cognitive Architecture for Human Robot Interaction. Within the team, your main responsibilities will be: * Exploiting functional memory networks and related AI in a cognitive architecture for better human robot collaboration; * Design of control systems for dextrose mobile robots aiming at natural human-robot collaboration; * Development of an AI solution for context awareness in collaborative unstructured manufacturing contexts; * Development of an AI solution for action planning in collaborative unstructured manufacturing contexts. This open position is financed by European Commission through HBP (Human Brain Project) project CEoI for SGA3 - Application of functional architectures supporting advanced cognitive functions to address AI and automation problems of industrial and commercial within the awarded PROMEN-AID, Proactive Memory iN AI for Development project (GA-94553) Please submit your application using the online form (https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=it&job=21000089 ) and including a detailed CV, cover letter (outlining motivation, experience and qualifications), names and contact of 2 referees. Application's deadline: January 16, 2022. -------------- next part -------------- An HTML attachment was scrubbed... URL: From juergen at idsia.ch Thu Dec 30 13:03:33 2021 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Thu, 30 Dec 2021 18:03:33 +0000 Subject: Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc. In-Reply-To: References: <33DC3654-F4D6-473C-9F95-FB99C483E89D@usi.ch> <15BAA8B8-0B89-4131-82B0-CFE4441EE55E@usi.ch> <48070117-2ABB-4CCD-ACC9-AF8C5811ED75@usi.ch> <11c3a52ca6ed4495a395ae019d8a0907@idsia.ch> <6093DADD-223B-44F1-8E8A-4E996838ED34@ucdavis.edu> <27D911A3-9C51-48A6-8034-7FF3A3E89BBB@princeton.edu> <2f1d9928-543f-f4a0-feab-5a5a0cc1d4d7@rubic.rutgers.edu> <307D9939-4F3A-40FF-A19F-3CEABEAE315C@supsi.ch> Message-ID: <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> Dear connectionists, in the wake of massive open online peer review, public comments on the connectionists mailing list [CONN21] and many additional private comments (some by well-known deep learning pioneers) helped to update and improve upon version 1 of the report. The essential statements of the text remain unchanged as their accuracy remains unchallenged. I'd like to thank everyone from the bottom of my heart for their feedback up until this point and hope everyone will be satisfied with the changes. Here is the revised version 2 with over 300 references: https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html In particular, Sec. II has become a brief history of deep learning up to the 1970s: Some of the most powerful NN architectures (i.e., recurrent NNs) were discussed in 1943 by McCulloch and Pitts [MC43] and formally analyzed in 1956 by Kleene [K56] - the closely related prior work in physics by Lenz, Ising, Kramers, and Wannier dates back to the 1920s [L20][I25][K41][W45]. In 1948, Turing wrote up ideas related to artificial evolution [TUR1] and learning NNs. He failed to formally publish his ideas though, which explains the obscurity of his thoughts here. Minsky's simple neural SNARC computer dates back to 1951. Rosenblatt's perceptron with a single adaptive layer learned in 1958 [R58] (Joseph [R61] mentions an earlier perceptron-like device by Farley & Clark); Widrow & Hoff's similar Adaline learned in 1962 [WID62]. Such single-layer "shallow learning" actually started around 1800 when Gauss & Legendre introduced linear regression and the method of least squares [DL1-2] - a famous early example of pattern recognition and generalization from training data through a parameterized predictor is Gauss' rediscovery of the asteroid Ceres based on previous astronomical observations. Deeper multilayer perceptrons (MLPs) were discussed by Steinbuch [ST61-95] (1961), Joseph [R61] (1961), and Rosenblatt [R62] (1962), who wrote about "back-propagating errors" in an MLP with a hidden layer [R62], but did not yet have a general deep learning algorithm for deep MLPs (what's now called backpropagation is quite different and was first published by Linnainmaa in 1970 [BP1-BP5][BPA-C]). Successful learning in deep architectures started in 1965 when Ivakhnenko & Lapa published the first general, working learning algorithms for deep MLPs with arbitrarily many hidden layers (already containing the now popular multiplicative gates) [DEEP1-2][DL1-2]. A paper of 1971 [DEEP2] already described a deep learning net with 8 layers, trained by their highly cited method which was still popular in the new millennium [DL2], especially in Eastern Europe, where much of Machine Learning was born [MIR](Sec. 1)[R8]. LBH failed to ci te this, just like they failed to cite Amari [GD1], who in 1967 proposed stochastic gradient descent [STO51-52] (SGD) for MLPs and whose implementation [GD2,GD2a] (with Saito) learned internal representations at a time when compute was billions of times more expensive than today (see also Tsypkin's work [GDa-b]). (In 1972, Amari also published what was later sometimes called the Hopfield network or Amari-Hopfield Network [AMH1-3].) Fukushima's now widely used deep convolutional NN architecture was first introduced in the 1970s [CNN1]. J?rgen ****************************** On 27 Oct 2021, at 10:52, Schmidhuber Juergen wrote: Hi, fellow artificial neural network enthusiasts! The connectionists mailing list is perhaps the oldest mailing list on ANNs, and many neural net pioneers are still subscribed to it. I am hoping that some of them - as well as their contemporaries - might be able to provide additional valuable insights into the history of the field. Following the great success of massive open online peer review (MOOR) for my 2015 survey of deep learning (now the most cited article ever published in the journal Neural Networks), I've decided to put forward another piece for MOOR. I want to thank the many experts who have already provided me with comments on it. Please send additional relevant references and suggestions for improvements for the following draft directly to me at juergen at idsia.ch: https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html The above is a point-for-point critique of factual errors in ACM's justification of the ACM A. M. Turing Award for deep learning and a critique of the Turing Lecture published by ACM in July 2021. This work can also be seen as a short history of deep learning, at least as far as ACM's errors and the Turing Lecture are concerned. I know that some view this as a controversial topic. However, it is the very nature of science to resolve controversies through facts. Credit assignment is as core to scientific history as it is to machine learning. My aim is to ensure that the true history of our field is preserved for posterity. Thank you all in advance for your help! J?rgen Schmidhuber From jose at rubic.rutgers.edu Thu Dec 30 18:28:19 2021 From: jose at rubic.rutgers.edu (=?UTF-8?Q?Stephen_Jos=c3=a9_Hanson?=) Date: Thu, 30 Dec 2021 18:28:19 -0500 Subject: Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc. In-Reply-To: <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> References: <33DC3654-F4D6-473C-9F95-FB99C483E89D@usi.ch> <15BAA8B8-0B89-4131-82B0-CFE4441EE55E@usi.ch> <48070117-2ABB-4CCD-ACC9-AF8C5811ED75@usi.ch> <11c3a52ca6ed4495a395ae019d8a0907@idsia.ch> <6093DADD-223B-44F1-8E8A-4E996838ED34@ucdavis.edu> <27D911A3-9C51-48A6-8034-7FF3A3E89BBB@princeton.edu> <2f1d9928-543f-f4a0-feab-5a5a0cc1d4d7@rubic.rutgers.edu> <307D9939-4F3A-40FF-A19F-3CEABEAE315C@supsi.ch> <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> Message-ID: Despite the comprehensive feel of this it still appears to me to be? too focused on Back-propagation per se.. (except for that pesky Gauss/Legendre ref--which still baffles me at least how this is related to a "neural network"), and at the same time it appears to be missing other more general epoch-conceptually relevant cases, say: Oliver Selfridge? and his Pandemonium model.. which was a hierarchical feature analysis system.. which certainly was in the air during the Neural network learning heyday...in fact, Minsky cites Selfridge as one of his mentors. Arthur Samuels:? Checker playing system.. which learned a evaluation function from a hierarchical search. Rosenblatt's advisor was Egon Brunswick.. who was a gestalt perceptual psychologist who introduced the concept that the world was stochastic and the the organism had to adapt to this variance somehow.. he called it "probabilistic functionalism"? which brought attention to learning, perception and decision theory, certainly all piece parts of what we call neural networks. There are many other such examples that influenced or provided context for the yeasty mix that was 1940s and 1950s where Neural Networks? first appeared partly due to PItts and McCulloch which entangled the human brain with computation and early computers themselves. I just don't see this as didactic, in the sense of a conceptual view of the? multidimensional history of the field, as opposed to? a 1-dimensional exegesis of mathematical threads through various statistical algorithms. Steve On 12/30/21 1:03 PM, Schmidhuber Juergen wrote: > Dear connectionists, > > in the wake of massive open online peer review, public comments on the connectionists mailing list [CONN21] and many additional private comments (some by well-known deep learning pioneers) helped to update and improve upon version 1 of the report. The essential statements of the text remain unchanged as their accuracy remains unchallenged. I'd like to thank everyone from the bottom of my heart for their feedback up until this point and hope everyone will be satisfied with the changes. Here is the revised version 2 with over 300 references: > > https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html > > In particular, Sec. II has become a brief history of deep learning up to the 1970s: > > Some of the most powerful NN architectures (i.e., recurrent NNs) were discussed in 1943 by McCulloch and Pitts [MC43] and formally analyzed in 1956 by Kleene [K56] - the closely related prior work in physics by Lenz, Ising, Kramers, and Wannier dates back to the 1920s [L20][I25][K41][W45]. In 1948, Turing wrote up ideas related to artificial evolution [TUR1] and learning NNs. He failed to formally publish his ideas though, which explains the obscurity of his thoughts here. Minsky's simple neural SNARC computer dates back to 1951. Rosenblatt's perceptron with a single adaptive layer learned in 1958 [R58] (Joseph [R61] mentions an earlier perceptron-like device by Farley & Clark); Widrow & Hoff's similar Adaline learned in 1962 [WID62]. Such single-layer "shallow learning" actually started around 1800 when Gauss & Legendre introduced linear regression and the method of least squares [DL1-2] - a famous early example of pattern recognition and generalization from training data t! > hrough a parameterized predictor is Gauss' rediscovery of the asteroid Ceres based on previous astronomical observations. Deeper multilayer perceptrons (MLPs) were discussed by Steinbuch [ST61-95] (1961), Joseph [R61] (1961), and Rosenblatt [R62] (1962), who wrote about "back-propagating errors" in an MLP with a hidden layer [R62], but did not yet have a general deep learning algorithm for deep MLPs (what's now called backpropagation is quite different and was first published by Linnainmaa in 1970 [BP1-BP5][BPA-C]). Successful learning in deep architectures started in 1965 when Ivakhnenko & Lapa published the first general, working learning algorithms for deep MLPs with arbitrarily many hidden layers (already containing the now popular multiplicative gates) [DEEP1-2][DL1-2]. A paper of 1971 [DEEP2] already described a deep learning net with 8 layers, trained by their highly cited method which was still popular in the new millennium [DL2], especially in Eastern Europe, wher! > e much of Machine Learning was born [MIR](Sec. 1)[R8]. LBH fai! > led to ci > te this, just like they failed to cite Amari [GD1], who in 1967 proposed stochastic gradient descent [STO51-52] (SGD) for MLPs and whose implementation [GD2,GD2a] (with Saito) learned internal representations at a time when compute was billions of times more expensive than today (see also Tsypkin's work [GDa-b]). (In 1972, Amari also published what was later sometimes called the Hopfield network or Amari-Hopfield Network [AMH1-3].) Fukushima's now widely used deep convolutional NN architecture was first introduced in the 1970s [CNN1]. > > J?rgen > > > > > ****************************** > > On 27 Oct 2021, at 10:52, Schmidhuber Juergen wrote: > > Hi, fellow artificial neural network enthusiasts! > > The connectionists mailing list is perhaps the oldest mailing list on ANNs, and many neural net pioneers are still subscribed to it. I am hoping that some of them - as well as their contemporaries - might be able to provide additional valuable insights into the history of the field. > > Following the great success of massive open online peer review (MOOR) for my 2015 survey of deep learning (now the most cited article ever published in the journal Neural Networks), I've decided to put forward another piece for MOOR. I want to thank the many experts who have already provided me with comments on it. Please send additional relevant references and suggestions for improvements for the following draft directly to me at juergen at idsia.ch: > > https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html > > The above is a point-for-point critique of factual errors in ACM's justification of the ACM A. M. Turing Award for deep learning and a critique of the Turing Lecture published by ACM in July 2021. This work can also be seen as a short history of deep learning, at least as far as ACM's errors and the Turing Lecture are concerned. > > I know that some view this as a controversial topic. However, it is the very nature of science to resolve controversies through facts. Credit assignment is as core to scientific history as it is to machine learning. My aim is to ensure that the true history of our field is preserved for posterity. > > Thank you all in advance for your help! > > J?rgen Schmidhuber > > > > -- -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.png Type: image/png Size: 19957 bytes Desc: not available URL: From juergen at idsia.ch Fri Dec 31 04:03:27 2021 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Fri, 31 Dec 2021 09:03:27 +0000 Subject: Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc. In-Reply-To: References: <33DC3654-F4D6-473C-9F95-FB99C483E89D@usi.ch> <15BAA8B8-0B89-4131-82B0-CFE4441EE55E@usi.ch> <48070117-2ABB-4CCD-ACC9-AF8C5811ED75@usi.ch> <11c3a52ca6ed4495a395ae019d8a0907@idsia.ch> <6093DADD-223B-44F1-8E8A-4E996838ED34@ucdavis.edu> <27D911A3-9C51-48A6-8034-7FF3A3E89BBB@princeton.edu> <2f1d9928-543f-f4a0-feab-5a5a0cc1d4d7@rubic.rutgers.edu> <307D9939-4F3A-40FF-A19F-3CEABEAE315C@supsi.ch> <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> Message-ID: Steve, this is not about machine learning in general, just about deep learning vs shallow learning. However, I added the Pandemonium - thanks for that! You ask: how is a linear regressor of 1800 (Gauss/Legendre) related to a linear neural network? It's formally equivalent, of course! (The only difference is that the weights are often called beta_i rather than w_i.) Shallow learning: one adaptive layer. Deep learning: many adaptive layers. Cheers, J?rgen > On 31 Dec 2021, at 00:28, Stephen Jos? Hanson wrote: > > Despite the comprehensive feel of this it still appears to me to be too focused on Back-propagation per se.. (except for that pesky Gauss/Legendre ref--which still baffles me at least how this is related to a "neural network"), and at the same time it appears to be missing other more general epoch-conceptually relevant cases, say: > > Oliver Selfridge and his Pandemonium model.. which was a hierarchical feature analysis system.. which certainly was in the air during the Neural network learning heyday...in fact, Minsky cites Selfridge as one of his mentors. > > Arthur Samuels: Checker playing system.. which learned a evaluation function from a hierarchical search. > > Rosenblatt's advisor was Egon Brunswick.. who was a gestalt perceptual psychologist who introduced the concept that the world was stochastic and the the organism had to adapt to this variance somehow.. he called it "probabilistic functionalism" which brought attention to learning, perception and decision theory, certainly all piece parts of what we call neural networks. > > There are many other such examples that influenced or provided context for the yeasty mix that was 1940s and 1950s where Neural Networks first appeared partly due to PItts and McCulloch which entangled the human brain with computation and early computers themselves. > > I just don't see this as didactic, in the sense of a conceptual view of the multidimensional history of the field, as opposed to a 1-dimensional exegesis of mathematical threads through various statistical algorithms. > > Steve > > On 12/30/21 1:03 PM, Schmidhuber Juergen wrote: >> Dear connectionists, >> >> in the wake of massive open online peer review, public comments on the connectionists mailing list [CONN21] and many additional private comments (some by well-known deep learning pioneers) helped to update and improve upon version 1 of the report. The essential statements of the text remain unchanged as their accuracy remains unchallenged. I'd like to thank everyone from the bottom of my heart for their feedback up until this point and hope everyone will be satisfied with the changes. Here is the revised version 2 with over 300 references: >> >> >> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >> >> >> In particular, Sec. II has become a brief history of deep learning up to the 1970s: >> >> Some of the most powerful NN architectures (i.e., recurrent NNs) were discussed in 1943 by McCulloch and Pitts [MC43] and formally analyzed in 1956 by Kleene [K56] - the closely related prior work in physics by Lenz, Ising, Kramers, and Wannier dates back to the 1920s [L20][I25][K41][W45]. In 1948, Turing wrote up ideas related to artificial evolution [TUR1] and learning NNs. He failed to formally publish his ideas though, which explains the obscurity of his thoughts here. Minsky's simple neural SNARC computer dates back to 1951. Rosenblatt's perceptron with a single adaptive layer learned in 1958 [R58] (Joseph [R61] mentions an earlier perceptron-like device by Farley & Clark); Widrow & Hoff's similar Adaline learned in 1962 [WID62]. Such single-layer "shallow learning" actually started around 1800 when Gauss & Legendre introduced linear regression and the method of least squares [DL1-2] - a famous early example of pattern recognition and generalization from training data through a parameterized predictor is Gauss' rediscovery of the asteroid Ceres based on previous astronomical observations. Deeper multilayer perceptrons (MLPs) were discussed by Steinbuch [ST61-95] (1961), Joseph [R61] (1961), and Rosenblatt [R62] (1962), who wrote about "back-propagating errors" in an MLP with a hidden layer [R62], but did not yet have a general deep learning algorithm for deep MLPs (what's now called backpropagation is quite different and was first published by Linnainmaa in 1970 [BP1-BP5][BPA-C]). Successful learning in deep architectures started in 1965 when Ivakhnenko & Lapa published the first general, working learning algorithms for deep MLPs with arbitrarily many hidden layers (already containing the now popular multiplicative gates) [DEEP1-2][DL1-2]. A paper of 1971 [DEEP2] already described a deep learning net with 8 layers, trained by their highly cited method which was still popular in the new millennium [DL2], especially in Eastern Europe, where much of Machine Learning was born [MIR](Sec. 1)[R8]. LBH failed to cite this, just like they failed to cite Amari [GD1], who in 1967 proposed stochastic gradient descent [STO51-52] (SGD) for MLPs and whose implementation [GD2,GD2a] (with Saito) learned internal representations at a time when compute was billions of times more expensive than today (see also Tsypkin's work [GDa-b]). (In 1972, Amari also published what was later sometimes called the Hopfield network or Amari-Hopfield Network [AMH1-3].) Fukushima's now widely used deep convolutional NN architecture was first introduced in the 1970s [CNN1]. >> >> J?rgen >> >> >> >> >> ****************************** >> >> On 27 Oct 2021, at 10:52, Schmidhuber Juergen >> >> wrote: >> >> Hi, fellow artificial neural network enthusiasts! >> >> The connectionists mailing list is perhaps the oldest mailing list on ANNs, and many neural net pioneers are still subscribed to it. I am hoping that some of them - as well as their contemporaries - might be able to provide additional valuable insights into the history of the field. >> >> Following the great success of massive open online peer review (MOOR) for my 2015 survey of deep learning (now the most cited article ever published in the journal Neural Networks), I've decided to put forward another piece for MOOR. I want to thank the many experts who have already provided me with comments on it. Please send additional relevant references and suggestions for improvements for the following draft directly to me at >> juergen at idsia.ch >> : >> >> >> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >> >> >> The above is a point-for-point critique of factual errors in ACM's justification of the ACM A. M. Turing Award for deep learning and a critique of the Turing Lecture published by ACM in July 2021. This work can also be seen as a short history of deep learning, at least as far as ACM's errors and the Turing Lecture are concerned. >> >> I know that some view this as a controversial topic. However, it is the very nature of science to resolve controversies through facts. Credit assignment is as core to scientific history as it is to machine learning. My aim is to ensure that the true history of our field is preserved for posterity. >> >> Thank you all in advance for your help! >> >> J?rgen Schmidhuber >> >> >> >> >> > -- > From epiasini at sissa.it Fri Dec 31 07:31:11 2021 From: epiasini at sissa.it (Eugenio Piasini) Date: Fri, 31 Dec 2021 12:31:11 +0000 Subject: Connectionists: Multiple PhD positions in Cognitive Neuroscience at SISSA Message-ID: [Apologies for cross?posting] Up to 6 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2022. SISSA is an elite postgraduate research institution for Maths, Physics and Neuroscience, located in Trieste, Italy. SISSA operates in English, and its faculty and student community is diverse and strongly international. The Cognitive Neuroscience Department hosts 7 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is highly interdisciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational, statistical and mathematical models. Students from a broad range of backgrounds (physics, maths, medicine, psychology, biology) are encouraged to apply. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator Davide Zoccolan (zoccolan at sissa.it) and/or your prospective supervisor for more information and informal enquiries. Best wishes, Eugenio Piasini -- Eugenio Piasini International School for Advanced Studies (SISSA) Via Bonomea 265, 34136 Trieste - Italy https://people.sissa.it/~epiasini From jose at rubic.rutgers.edu Fri Dec 31 12:24:07 2021 From: jose at rubic.rutgers.edu (=?UTF-8?Q?Stephen_Jos=c3=a9_Hanson?=) Date: Fri, 31 Dec 2021 12:24:07 -0500 Subject: Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc. In-Reply-To: References: <15BAA8B8-0B89-4131-82B0-CFE4441EE55E@usi.ch> <48070117-2ABB-4CCD-ACC9-AF8C5811ED75@usi.ch> <11c3a52ca6ed4495a395ae019d8a0907@idsia.ch> <6093DADD-223B-44F1-8E8A-4E996838ED34@ucdavis.edu> <27D911A3-9C51-48A6-8034-7FF3A3E89BBB@princeton.edu> <2f1d9928-543f-f4a0-feab-5a5a0cc1d4d7@rubic.rutgers.edu> <307D9939-4F3A-40FF-A19F-3CEABEAE315C@supsi.ch> <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> Message-ID: Well the perceptron is closer to logistic regression... but the heaviside function? of course is <0,1>?? so technically not related to linear regression which is using covariance to estimate betas... does that matter?? Yes, if you want to be hyper correct--as this appears to be-- Berkson (1944) coined the logit.. as log odds.. for probabilistic classification.. this was formally developed by Cox in the early 60s, so unlikely even in this case to be a precursor to perceptron. My point was that DL requires both Learning algorithm (BP) and an architecture.. which seems to me much more responsible for the the success of Dl. S On 12/31/21 4:03 AM, Schmidhuber Juergen wrote: > Steve, this is not about machine learning in general, just about deep learning vs shallow learning. However, I added the Pandemonium - thanks for that! You ask: how is a linear regressor of 1800 (Gauss/Legendre) related to a linear neural network? It's formally equivalent, of course! (The only difference is that the weights are often called beta_i rather than w_i.) Shallow learning: one adaptive layer. Deep learning: many adaptive layers. Cheers, J?rgen > > > >> On 31 Dec 2021, at 00:28, Stephen Jos? Hanson wrote: >> >> Despite the comprehensive feel of this it still appears to me to be too focused on Back-propagation per se.. (except for that pesky Gauss/Legendre ref--which still baffles me at least how this is related to a "neural network"), and at the same time it appears to be missing other more general epoch-conceptually relevant cases, say: >> >> Oliver Selfridge and his Pandemonium model.. which was a hierarchical feature analysis system.. which certainly was in the air during the Neural network learning heyday...in fact, Minsky cites Selfridge as one of his mentors. >> >> Arthur Samuels: Checker playing system.. which learned a evaluation function from a hierarchical search. >> >> Rosenblatt's advisor was Egon Brunswick.. who was a gestalt perceptual psychologist who introduced the concept that the world was stochastic and the the organism had to adapt to this variance somehow.. he called it "probabilistic functionalism" which brought attention to learning, perception and decision theory, certainly all piece parts of what we call neural networks. >> >> There are many other such examples that influenced or provided context for the yeasty mix that was 1940s and 1950s where Neural Networks first appeared partly due to PItts and McCulloch which entangled the human brain with computation and early computers themselves. >> >> I just don't see this as didactic, in the sense of a conceptual view of the multidimensional history of the field, as opposed to a 1-dimensional exegesis of mathematical threads through various statistical algorithms. >> >> Steve >> >> On 12/30/21 1:03 PM, Schmidhuber Juergen wrote: >>> Dear connectionists, >>> >>> in the wake of massive open online peer review, public comments on the connectionists mailing list [CONN21] and many additional private comments (some by well-known deep learning pioneers) helped to update and improve upon version 1 of the report. The essential statements of the text remain unchanged as their accuracy remains unchallenged. I'd like to thank everyone from the bottom of my heart for their feedback up until this point and hope everyone will be satisfied with the changes. Here is the revised version 2 with over 300 references: >>> >>> >>> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >>> >>> >>> In particular, Sec. II has become a brief history of deep learning up to the 1970s: >>> >>> Some of the most powerful NN architectures (i.e., recurrent NNs) were discussed in 1943 by McCulloch and Pitts [MC43] and formally analyzed in 1956 by Kleene [K56] - the closely related prior work in physics by Lenz, Ising, Kramers, and Wannier dates back to the 1920s [L20][I25][K41][W45]. In 1948, Turing wrote up ideas related to artificial evolution [TUR1] and learning NNs. He failed to formally publish his ideas though, which explains the obscurity of his thoughts here. Minsky's simple neural SNARC computer dates back to 1951. Rosenblatt's perceptron with a single adaptive layer learned in 1958 [R58] (Joseph [R61] mentions an earlier perceptron-like device by Farley & Clark); Widrow & Hoff's similar Adaline learned in 1962 [WID62]. Such single-layer "shallow learning" actually started around 1800 when Gauss & Legendre introduced linear regression and the method of least squares [DL1-2] - a famous early example of pattern recognition and generalization from training dat! > a through a parameterized predictor is Gauss' rediscovery of the asteroid Ceres based on previous astronomical observations. Deeper multilayer perceptrons (MLPs) were discussed by Steinbuch [ST61-95] (1961), Joseph [R61] (1961), and Rosenblatt [R62] (1962), who wrote about "back-propagating errors" in an MLP with a hidden layer [R62], but did not yet have a general deep learning algorithm for deep MLPs (what's now called backpropagation is quite different and was first published by Linnainmaa in 1970 [BP1-BP5][BPA-C]). Successful learning in deep architectures started in 1965 when Ivakhnenko & Lapa published the first general, working learning algorithms for deep MLPs with arbitrarily many hidden layers (already containing the now popular multiplicative gates) [DEEP1-2][DL1-2]. A paper of 1971 [DEEP2] already described a deep learning net with 8 layers, trained by their highly cited method which was still popular in the new millennium [DL2], especially in Eastern Europe, w! > here much of Machine Learning was born [MIR](Sec. 1)[R8]. LBH ! > failed to > cite this, just like they failed to cite Amari [GD1], who in 1967 proposed stochastic gradient descent [STO51-52] (SGD) for MLPs and whose implementation [GD2,GD2a] (with Saito) learned internal representations at a time when compute was billions of times more expensive than today (see also Tsypkin's work [GDa-b]). (In 1972, Amari also published what was later sometimes called the Hopfield network or Amari-Hopfield Network [AMH1-3].) Fukushima's now widely used deep convolutional NN architecture was first introduced in the 1970s [CNN1]. >>> J?rgen >>> >>> >>> >>> >>> ****************************** >>> >>> On 27 Oct 2021, at 10:52, Schmidhuber Juergen >>> >>> wrote: >>> >>> Hi, fellow artificial neural network enthusiasts! >>> >>> The connectionists mailing list is perhaps the oldest mailing list on ANNs, and many neural net pioneers are still subscribed to it. I am hoping that some of them - as well as their contemporaries - might be able to provide additional valuable insights into the history of the field. >>> >>> Following the great success of massive open online peer review (MOOR) for my 2015 survey of deep learning (now the most cited article ever published in the journal Neural Networks), I've decided to put forward another piece for MOOR. I want to thank the many experts who have already provided me with comments on it. Please send additional relevant references and suggestions for improvements for the following draft directly to me at >>> juergen at idsia.ch >>> : >>> >>> >>> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >>> >>> >>> The above is a point-for-point critique of factual errors in ACM's justification of the ACM A. M. Turing Award for deep learning and a critique of the Turing Lecture published by ACM in July 2021. This work can also be seen as a short history of deep learning, at least as far as ACM's errors and the Turing Lecture are concerned. >>> >>> I know that some view this as a controversial topic. However, it is the very nature of science to resolve controversies through facts. Credit assignment is as core to scientific history as it is to machine learning. My aim is to ensure that the true history of our field is preserved for posterity. >>> >>> Thank you all in advance for your help! >>> >>> J?rgen Schmidhuber >>> >>> >>> >>> >>> >> -- >> > -- -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.png Type: image/png Size: 19957 bytes Desc: not available URL: From juergen at idsia.ch Fri Dec 31 12:59:57 2021 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Fri, 31 Dec 2021 17:59:57 +0000 Subject: Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc. In-Reply-To: References: <15BAA8B8-0B89-4131-82B0-CFE4441EE55E@usi.ch> <48070117-2ABB-4CCD-ACC9-AF8C5811ED75@usi.ch> <11c3a52ca6ed4495a395ae019d8a0907@idsia.ch> <6093DADD-223B-44F1-8E8A-4E996838ED34@ucdavis.edu> <27D911A3-9C51-48A6-8034-7FF3A3E89BBB@princeton.edu> <2f1d9928-543f-f4a0-feab-5a5a0cc1d4d7@rubic.rutgers.edu> <307D9939-4F3A-40FF-A19F-3CEABEAE315C@supsi.ch> <2293D07C-A5E3-4E66-9120-C14DE15239A7@supsi.ch> Message-ID: <29BC825D-F353-457A-A9FD-9F25F3D1A6DB@supsi.ch> Sure, Steve, perceptron/Adaline/other similar methods of the 1950s/60s are not quite the same, but the obvious origin and ancestor of all those single-layer ?shallow learning? architectures/methods is indeed linear regression; today?s simplest NNs minimizing mean squared error are exactly what they had 2 centuries ago. And the first working deep learning methods of the 1960s did NOT really require ?modern? backprop (published in 1970 by Linnainmaa [BP1-5]). For example, Ivakhnenko & Lapa (1965) [DEEP1-2] incrementally trained and pruned their deep networks layer by layer to learn internal representations, using regression and a separate validation set. Amari (1967-68)[GD1] used stochastic gradient descent [STO51-52] to learn internal representations WITHOUT ?modern" backprop in his multilayer perceptrons. J?rgen > On 31 Dec 2021, at 18:24, Stephen Jos? Hanson wrote: > > Well the perceptron is closer to logistic regression... but the heaviside function of course is <0,1> so technically not related to linear regression which is using covariance to estimate betas... > > does that matter? Yes, if you want to be hyper correct--as this appears to be-- Berkson (1944) coined the logit.. as log odds.. for probabilistic classification.. this was formally developed by Cox in the early 60s, so unlikely even in this case to be a precursor to perceptron. > > My point was that DL requires both Learning algorithm (BP) and an architecture.. which seems to me much more responsible for the > the success of Dl. > > S > > > > On 12/31/21 4:03 AM, Schmidhuber Juergen wrote: >> Steve, this is not about machine learning in general, just about deep learning vs shallow learning. However, I added the Pandemonium - thanks for that! You ask: how is a linear regressor of 1800 (Gauss/Legendre) related to a linear neural network? It's formally equivalent, of course! (The only difference is that the weights are often called beta_i rather than w_i.) Shallow learning: one adaptive layer. Deep learning: many adaptive layers. Cheers, J?rgen >> >> >> >> >>> On 31 Dec 2021, at 00:28, Stephen Jos? Hanson >>> wrote: >>> >>> Despite the comprehensive feel of this it still appears to me to be too focused on Back-propagation per se.. (except for that pesky Gauss/Legendre ref--which still baffles me at least how this is related to a "neural network"), and at the same time it appears to be missing other more general epoch-conceptually relevant cases, say: >>> >>> Oliver Selfridge and his Pandemonium model.. which was a hierarchical feature analysis system.. which certainly was in the air during the Neural network learning heyday...in fact, Minsky cites Selfridge as one of his mentors. >>> >>> Arthur Samuels: Checker playing system.. which learned a evaluation function from a hierarchical search. >>> >>> Rosenblatt's advisor was Egon Brunswick.. who was a gestalt perceptual psychologist who introduced the concept that the world was stochastic and the the organism had to adapt to this variance somehow.. he called it "probabilistic functionalism" which brought attention to learning, perception and decision theory, certainly all piece parts of what we call neural networks. >>> >>> There are many other such examples that influenced or provided context for the yeasty mix that was 1940s and 1950s where Neural Networks first appeared partly due to PItts and McCulloch which entangled the human brain with computation and early computers themselves. >>> >>> I just don't see this as didactic, in the sense of a conceptual view of the multidimensional history of the field, as opposed to a 1-dimensional exegesis of mathematical threads through various statistical algorithms. >>> >>> Steve >>> >>> On 12/30/21 1:03 PM, Schmidhuber Juergen wrote: >>> >>>> Dear connectionists, >>>> >>>> in the wake of massive open online peer review, public comments on the connectionists mailing list [CONN21] and many additional private comments (some by well-known deep learning pioneers) helped to update and improve upon version 1 of the report. The essential statements of the text remain unchanged as their accuracy remains unchallenged. I'd like to thank everyone from the bottom of my heart for their feedback up until this point and hope everyone will be satisfied with the changes. Here is the revised version 2 with over 300 references: >>>> >>>> >>>> >>>> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >>>> >>>> >>>> >>>> In particular, Sec. II has become a brief history of deep learning up to the 1970s: >>>> >>>> Some of the most powerful NN architectures (i.e., recurrent NNs) were discussed in 1943 by McCulloch and Pitts [MC43] and formally analyzed in 1956 by Kleene [K56] - the closely related prior work in physics by Lenz, Ising, Kramers, and Wannier dates back to the 1920s [L20][I25][K41][W45]. In 1948, Turing wrote up ideas related to artificial evolution [TUR1] and learning NNs. He failed to formally publish his ideas though, which explains the obscurity of his thoughts here. Minsky's simple neural SNARC computer dates back to 1951. Rosenblatt's perceptron with a single adaptive layer learned in 1958 [R58] (Joseph [R61] mentions an earlier perceptron-like device by Farley & Clark); Widrow & Hoff's similar Adaline learned in 1962 [WID62]. Such single-layer "shallow learning" actually started around 1800 when Gauss & Legendre introduced linear regression and the method of least squares [DL1-2] - a famous early example of pattern recognition and generalization from training dat! >>>> >> a through a parameterized predictor is Gauss' rediscovery of the asteroid Ceres based on previous astronomical observations. Deeper multilayer perceptrons (MLPs) were discussed by Steinbuch [ST61-95] (1961), Joseph [R61] (1961), and Rosenblatt [R62] (1962), who wrote about "back-propagating errors" in an MLP with a hidden layer [R62], but did not yet have a general deep learning algorithm for deep MLPs (what's now called backpropagation is quite different and was first published by Linnainmaa in 1970 [BP1-BP5][BPA-C]). Successful learning in deep architectures started in 1965 when Ivakhnenko & Lapa published the first general, working learning algorithms for deep MLPs with arbitrarily many hidden layers (already containing the now popular multiplicative gates) [DEEP1-2][DL1-2]. A paper of 1971 [DEEP2] already described a deep learning net with 8 layers, trained by their highly cited method which was still popular in the new millennium [DL2], especially in Eastern Europe, w! >> here much of Machine Learning was born [MIR](Sec. 1)[R8]. LBH ! >> failed to >> cite this, just like they failed to cite Amari [GD1], who in 1967 proposed stochastic gradient descent [STO51-52] (SGD) for MLPs and whose implementation [GD2,GD2a] (with Saito) learned internal representations at a time when compute was billions of times more expensive than today (see also Tsypkin's work [GDa-b]). (In 1972, Amari also published what was later sometimes called the Hopfield network or Amari-Hopfield Network [AMH1-3].) Fukushima's now widely used deep convolutional NN architecture was first introduced in the 1970s [CNN1]. >> >>>> J?rgen >>>> >>>> >>>> >>>> >>>> ****************************** >>>> >>>> On 27 Oct 2021, at 10:52, Schmidhuber Juergen >>>> >>>> >>>> >>>> wrote: >>>> >>>> Hi, fellow artificial neural network enthusiasts! >>>> >>>> The connectionists mailing list is perhaps the oldest mailing list on ANNs, and many neural net pioneers are still subscribed to it. I am hoping that some of them - as well as their contemporaries - might be able to provide additional valuable insights into the history of the field. >>>> >>>> Following the great success of massive open online peer review (MOOR) for my 2015 survey of deep learning (now the most cited article ever published in the journal Neural Networks), I've decided to put forward another piece for MOOR. I want to thank the many experts who have already provided me with comments on it. Please send additional relevant references and suggestions for improvements for the following draft directly to me at >>>> >>>> juergen at idsia.ch >>>> >>>> : >>>> >>>> >>>> >>>> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html >>>> >>>> >>>> >>>> The above is a point-for-point critique of factual errors in ACM's justification of the ACM A. M. Turing Award for deep learning and a critique of the Turing Lecture published by ACM in July 2021. This work can also be seen as a short history of deep learning, at least as far as ACM's errors and the Turing Lecture are concerned. >>>> >>>> I know that some view this as a controversial topic. However, it is the very nature of science to resolve controversies through facts. Credit assignment is as core to scientific history as it is to machine learning. My aim is to ensure that the true history of our field is preserved for posterity. >>>> >>>> Thank you all in advance for your help! >>>> >>>> J?rgen Schmidhuber >>>> >>>> >>>> >>>> >>>> >>>> >>> -- >>> >>> >> > -- >