Connectionists: ESANN 2024 SS CFP - Informed Machine Learning for Complex Data

[Luca Oneto]

[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

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:
Submission of papers: 2 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 (Università di Pisa, Italy)
Luca Pasa (University of Padova, Italy)
Claudio Gallicchio (University of Pisa, Italy)
Davide Bacciu (Università di Pisa, Italy)
Davide Anguita (DIBRIS - University of Genova, Italy)

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Prof. Luca Oneto
University of Genoa
www.lucaoneto.it
luca.oneto at unige.it
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