Connectionists: Call for Papers: deadline extended special session on "Informed Machine Learning for Complex Data" at ESANN 2024

[Nicolo' Navarin]

[Apologies if you receive multiple copies of this CFP]

Call for papers: special session on "Informed Machine Learning for Complex Data" at ESANN 2024 - https://www.esann.org/special-sessions

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2024).
9-11 October 2024, Bruges, Belgium - http://www.esann.org <http://www.esann.org/>

DESCRIPTION:
In the contemporary era of data-driven decision-making, the application of Machine Learning (ML) on complex data (e.g., images, text, sequences, trees, and graphs) has become increasingly pivotal (e.g., LLM and GraphNN for Drugs Discovery). In this context, there is a gap between purely data-driven models and domain-specific knowledge, requirements, and expertise. In particular, this domain specificity needs to be integrated into the ML models to improve learning generalization, sustainability, trustworthiness, reliability, security, and safety. This additional knowledge can assume different forms, e.g.:
- software developers require ML to comply with many technical requirements;
- companies require ML to comply with economic and environmental sustainability;
- domain experts require ML to be aligned with physical and logical laws;
- society requires ML to be aligned with ethical principles.
This special session aims to gather valuable contributions and early findings in the field of Informed Machine Learning for Complex Data. Our main objective is to showcase the potential and limitations of new ideas, improvements, or the blending of Artificial Intelligence, Machine  Learning, and other research areas in solving real-world problems. We invite both theoretical and practical results to this special session.

TOPICS OF INTEREST:
- Data-informed ML (e.g., the ability to directly learn from complex data)
- Technically-informed ML (e.g., regressiveness, replicability, and security)
- Sustainability-informed ML (e.g., ability to learn and predict efficiently from data)
- Knowledge-informed ML (e.g., physical laws, logical requirements, and algorithms)
- Ethically-informed ML (e.g., fairness, explainability, fairness, and cultural competence)

SUBMISSION:
Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.esann.org/node/6  
Each paper will undergo a peer reviewing process for its acceptance.

IMPORTANT DATES:
EXTENDED Submission of papers: 6 May 2024
Notification of acceptance: 16 June 2024
ESANN conference: 9-11 October 2024

SPECIAL SESSION ORGANISERS:
Luca Oneto (University of Genoa, Italy)
Nicolò Navarin (University of Padua, Italy)
Alessio Micheli (University of Pisa, Italy)
Luca Pasa (University of Padova, Italy)
Claudio Gallicchio (University of Pisa, Italy)
Davide Bacciu (University of Pisa, Italy)
Davide Anguita (DIBRIS - University of Genova, Italy)
—
Nicolò Navarin, Ph.D.

Associate Professor of Computer Science
University of Padua - Department of Mathematics
via Trieste 63, 35121 Padova - Italy
Office: 3CD2
Tel.  +39 049  8271384
E-mail:  nicolo.navarin at unipd.it
Zoom: https://unipd.zoom.us/my/navarin
Web: http://www.math.unipd.it/~nnavarin

CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents.
Towards a sustainable earth: Print only when necessary. Thank you.



—
Nicolò Navarin, Ph.D.

Associate Professor of Computer Science
University of Padua - Department of Mathematics
via Trieste 63, 35121 Padova - Italy
Office: 3CD2
Tel.  +39 049  8271384
E-mail:  nicolo.navarin at unipd.it
Zoom: https://unipd.zoom.us/my/navarin
Web: http://www.math.unipd.it/~nnavarin

CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents.
Towards a sustainable earth: Print only when necessary. Thank you.

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