<meta http-equiv="Content-Type" content="text/html; charset=utf-8"><div dir="ltr"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">[Apologies if you receive multiple copies of this CFP]</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Call for papers: special session on "Informed Machine Learning for Complex Data" at ESANN 2024 - <a href="https://www.esann.org/special-sessions">https://www.esann.org/special-sessions</a></span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2024).</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">9-11 October 2024, Bruges, Belgium - <a href="http://www.esann.org">http://www.esann.org</a></span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">DESCRIPTION:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">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.:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- software developers require ML to comply with many technical requirements;</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- companies require ML to comply with economic and environmental sustainability;</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- domain experts require ML to be aligned with physical and logical laws;</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- society requires ML to be aligned with ethical principles.</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">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.</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">TOPICS OF INTEREST:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- Data-informed ML (e.g., the ability to directly learn from complex data)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- Technically-informed ML (e.g., regressiveness, replicability, and security)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- Sustainability-informed ML (e.g., ability to learn and predict efficiently from data)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- Knowledge-informed ML (e.g., physical laws, logical requirements, and algorithms)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">- Ethically-informed ML (e.g., fairness, explainability, fairness, and cultural competence)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">SUBMISSION:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Prospective authors must submit their paper through the ESANN portal following the instructions provided in <a href="https://www.esann.org/node/6">https://www.esann.org/node/6</a>  Each paper will undergo a peer reviewing process for its acceptance.</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">IMPORTANT DATES:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Submission of papers: 2 May 2024</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Notification of acceptance: 16 June 2024</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">ESANN conference: 9-11 October 2024</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">SPECIAL SESSION ORGANISERS:</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Luca Oneto (University of Genoa, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Nicolò Navarin (University of Padua, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Alessio Micheli (Università di Pisa, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Luca Pasa (University of Padova, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Claudio Gallicchio (University of Pisa, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Davide Bacciu (Università di Pisa, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Davide Anguita (DIBRIS - University of Genova, Italy)</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">----------------------------------------</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Prof. Luca Oneto</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">University of Genoa</span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><a href="http://www.lucaoneto.it">www.lucaoneto.it</a></span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><a href="mailto:luca.oneto@unige.it">luca.oneto@unige.it</a></span><br style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px"><span style="color:rgba(0,0,0,0.87);font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">----------------------------------------</span><br></div>