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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal>[Apologies for cross-postings]<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>###########################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>The INNS Big Data conference 2016<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>October 23-25, 2016, Thessaloniki, Greece<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>CALL FOR PAPERS<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>###########################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Homepage: http://www.innsbigdata.org<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>###########################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Big data is not just about storage of and access to data. Analytics play a big role in making sense<o:p></o:p></p><p class=MsoNormal>of that data and exploiting its value. But learning from big data has become a significant challenge<o:p></o:p></p><p class=MsoNormal>and requires development of new types of algorithms. Most machine learning algorithms can’t easily<o:p></o:p></p><p class=MsoNormal>scale up to big data. Plus there are challenges of high-dimensionality, velocity and variety. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>The neural network field has historically focused on algorithms that learn in an online, incremental mode<o:p></o:p></p><p class=MsoNormal>without requiring in-memory access to huge amounts of data. This type of learning is not only ideal<o:p></o:p></p><p class=MsoNormal>for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used<o:p></o:p></p><p class=MsoNormal>on stored big data. Neural network technologies thus can become significant components of big<o:p></o:p></p><p class=MsoNormal>data analytics platforms and this inaugural INNS Conference on Big Data will begin that collaborative<o:p></o:p></p><p class=MsoNormal>adventure with big data and other learning technologies. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Thus the aim of this conference is to<o:p></o:p></p><p class=MsoNormal>promote new advances and research directions in efficient and innovative algorithmic approaches to<o:p></o:p></p><p class=MsoNormal>analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations<o:p></o:p></p><p class=MsoNormal>on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications<o:p></o:p></p><p class=MsoNormal>of Big Data Analytics to solve real-world problems (e.g. weather prediction, transportation, energy<o:p></o:p></p><p class=MsoNormal>management).<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Awards<o:p></o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal>* Best papers will be selected and awarded as follows:<o:p></o:p></p><p class=MsoNormal>- Best regular paper<o:p></o:p></p><p class=MsoNormal>- Best student paper<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>* This will be based on a combination of reviewers' comments, presentations and importance and quality judged by a panel. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>* Best paper awards (500 Euros) are donated by the sponsor Springer Verlag, Germany and will be commemorated by a certificate.<o:p></o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Important Dates<o:p></o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal>Special Session Proposals February 15, 2016<o:p></o:p></p><p class=MsoNormal>Tutorials and Workshops Proposals February 15, 2016<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Paper Submission March 21, 2016<o:p></o:p></p><p class=MsoNormal>Paper Decision Notification May 16, 2016<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Camera Ready Submission of papers June 13, 2016<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Co-Sponsors<o:p></o:p></p><p class=MsoNormal>* International Neural Network Society (INNS)<o:p></o:p></p><p class=MsoNormal>* Springer<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Plenary Speakers<o:p></o:p></p><p class=MsoNormal>* Francesco Bonchi, Yahoo Research Labs and ISI, Italy<o:p></o:p></p><p class=MsoNormal>* Piotr Mirowski, Google DeepMind, London, UK<o:p></o:p></p><p class=MsoNormal>* Hany Choueri, The Chief Data Scientist, Bank of England, UK (tbc)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Advisory Board<o:p></o:p></p><p class=MsoNormal>* Walter Freeman, University of California, Berkeley, USA<o:p></o:p></p><p class=MsoNormal>* Ali Minai, University of Cincinnati, USA<o:p></o:p></p><p class=MsoNormal>* Danil Prokhorov, Toyota Tech Center <o:p></o:p></p><p class=MsoNormal>* Theodore Trafalis, University of Oklahoma, USA<o:p></o:p></p><p class=MsoNormal>* Kumar Venayagamoorthy, Clemson University, USA<o:p></o:p></p><p class=MsoNormal>* Bernard Widrow, Stanford University, USA<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>General Chairs<o:p></o:p></p><p class=MsoNormal>* Plamen Angelov, Lancaster University, UK<o:p></o:p></p><p class=MsoNormal>* Yannis Manolopoulos, Aristotle University, Greece<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>PC Chairs<o:p></o:p></p><p class=MsoNormal>* Lazaros Iliadias, Democritus University, Greece<o:p></o:p></p><p class=MsoNormal>* Asim Roy, Arizona State University, Tempe, USA<o:p></o:p></p><p class=MsoNormal>* Marley Vellasco, PUC-Rio, Rio de Janeiro, Brazil<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Special Sessions Chairs<o:p></o:p></p><p class=MsoNormal>* Alessandro Ghio, University of Genoa, Italy<o:p></o:p></p><p class=MsoNormal>* Irwin King, Chinese University of Hong Kong, China<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Tutorials/Workshops Chair<o:p></o:p></p><p class=MsoNormal>* Nikola Kasabov, Auckland Universitty of Technology, New Zealand<o:p></o:p></p><p class=MsoNormal>* Bernardete Ribeiro, University of Coimbra, Portugal<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Poster Session Chairs<o:p></o:p></p><p class=MsoNormal>* Yi Lu Murphy, University of Michigan-Dearborn, USA<o:p></o:p></p><p class=MsoNormal>* Liang Zhao, University of Sao Paulo, Brazil<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Awards Chair<o:p></o:p></p><p class=MsoNormal>* Araceli Sanchis de Miguel, Carlos III University, Spain<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Competitions Chair<o:p></o:p></p><p class=MsoNormal>Adel Alimi, University of Sfax, Tunisia<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Panel Chair<o:p></o:p></p><p class=MsoNormal>* Leonid Perlovsky, Harvard University, Boston, USA<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Sponsors/Exhibit Chairs<o:p></o:p></p><p class=MsoNormal>* James Dankert, BAE Systems, USA<o:p></o:p></p><p class=MsoNormal>* Rosemary Paradis, Lockheed Martin, USA<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Publication Chairs<o:p></o:p></p><p class=MsoNormal>* Danilo Mandic, Imperial College, London, UK<o:p></o:p></p><p class=MsoNormal>* Mariette Awad, American University of Beirut, Lebanon<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>International Liaison <o:p></o:p></p><p class=MsoNormal>* De-Shuang Huang, Tongji University, Shanghai, China<o:p></o:p></p><p class=MsoNormal>* Petia Georgieva, University of Aveiro, Portugal<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Publicity Chairs,<o:p></o:p></p><p class=MsoNormal>* Teng Teck Hou, Singapore Management University, Singapore<o:p></o:p></p><p class=MsoNormal>* Simone Scardapane, The Sapienza University of Rome, Italy<o:p></o:p></p><p class=MsoNormal>* Jose Antonio Iglesias Martinez, Carlos III University, Spain<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Paper Submission and Publication<o:p></o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal>* Original works submitted as a regular paper limited to a maximum of 10 pages in Springer format will be published in the proceedings to be available electronically as a Springer book to download for delegates. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>* It will be peer-reviewed by at least three PC members on the basis of technical quality, relevance, originality, significance and clarity. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>* At least one author of an accepted submission to the conference should register with a regular fee to present their work at the conference.<o:p></o:p></p><p class=MsoNormal>###########################################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Topics and Areas include, but not limited to:<o:p></o:p></p><p class=MsoNormal>* Autonomous, online, incremental learning – theory, algorithms and applications in big data<o:p></o:p></p><p class=MsoNormal>* High dimensional data, feature selection, feature transformation – theory, algorithms and applications<o:p></o:p></p><p class=MsoNormal>for big data<o:p></o:p></p><p class=MsoNormal>* Scalable algorithms for big data<o:p></o:p></p><p class=MsoNormal>* Learning algorithms for high-velocity streaming data<o:p></o:p></p><p class=MsoNormal>* Big data streams analytics<o:p></o:p></p><p class=MsoNormal>* Deep neural network learning<o:p></o:p></p><p class=MsoNormal>* Machine vision and big data<o:p></o:p></p><p class=MsoNormal>* Brain-machine interfaces and big data<o:p></o:p></p><p class=MsoNormal>* Cognitive modeling and big data<o:p></o:p></p><p class=MsoNormal>* Embodied robotics and big data<o:p></o:p></p><p class=MsoNormal>* Fuzzy systems and big data<o:p></o:p></p><p class=MsoNormal>* Evolutionary systems and big data<o:p></o:p></p><p class=MsoNormal>* Evolving systems for big data analytics<o:p></o:p></p><p class=MsoNormal>* Neuromorphic hardware for scalable machine learning<o:p></o:p></p><p class=MsoNormal>* Parallel and distributed computing for big data analytics (cloud, map-reduce, etc.)<o:p></o:p></p><p class=MsoNormal>* Big data and collective intelligence/collaborative learning<o:p></o:p></p><p class=MsoNormal>* Big data and hybrid systems<o:p></o:p></p><p class=MsoNormal>* Big data and self-aware systems<o:p></o:p></p><p class=MsoNormal>* Big Data and infrastructure<o:p></o:p></p><p class=MsoNormal>* Big data analytics and healthcare/medical applications<o:p></o:p></p><p class=MsoNormal>* Big data analytics and energy systems/smart grids<o:p></o:p></p><p class=MsoNormal>* Big data analytics and transportation systems<o:p></o:p></p><p class=MsoNormal>* Big data analytics in large sensor networks<o:p></o:p></p><p class=MsoNormal>* Big data and machine learning in computational biology, bioinformatics<o:p></o:p></p><p class=MsoNormal>* Recommendation systems/collaborative filtering for big data<o:p></o:p></p><p class=MsoNormal>* Big data visualization<o:p></o:p></p><p class=MsoNormal>* Online multimedia/ stream/ text analytics<o:p></o:p></p><p class=MsoNormal>* Link and graph mining<o:p></o:p></p><p class=MsoNormal>* Big data and cloud computing, large scale stream processing on the cloud<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>