Motivated by the observation that machine learning can be thought of as “a continuation of epistemology by other means” (liberally adapted from Carl von Clausewitz) in this tutorial we will try to critically examine some of the most fundamental (and often tacit) assumptions of machine learning through a philosopher’s lens. In particular, we will focus on key questions pertaining to induction, confirmation, causality, and explanation.
27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE
19-24 OCTOBER 2024
Santiago de Compostela
The Epistemology of Machine Learning: Induction, Causality, Explanation
Marcello Pelillo is a Full Professor of Computer Science at Ca’ Foscari University, Venice, where he leads the Computer Vision and Machine Learning Lab which he established in 1995. He has been the Director of the European Centre for Living Technology (ECLT) and has held visiting
research/teaching positions at Yale University (USA), McGill University (Canada), University
College London (UK), University of Vienna (Austria), York University (UK), NICTA (Australia),
Wuhan University (China), Huazhong University of Science and Technology (Wuhan, China), South China University of Technology (Guangzhou, China). He is an external affiliate of the Computer Science Department at Drexel University (USA) and of the Italian Institute of Technology. His research interests are in the areas of computer vision, machine learning, and pattern recognition where he has published more than 300 technical papers in refereed journals, handbooks, and conference proceedings.
He has been the General Chair for ICCV 2017 and Program Chair for ICPR 2020. He has also been Track Chair for ICPR 2018 and is regularly an Area Chair for the top-tier conferences in his field (ICCV, ECCV, CVPR, IJCAI, ICPR, etc.). He has served as Program Chair for several conferences, including workshops at NIPS (1999, 2011) and ICML (2010), many of which he initiated (e.g., EMMCVPR, SIMBAD, IWCV). He is the Chief Editor of Frontiers in Computer Science – Computer Vision, and serves or has served on the Editorial Boards of several journals, including IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition, IET Computer Vision, Frontiers in Computer Image Analysis, Brain Informatics, IEEE Transactions on Neural Networks and Learning Systems (Guest Editor), Pattern Recognition Letters (Guest Editor), and serves on the Advisory Board of Springer’s International Journal of Machine Learning and Cybernetics. He is regularly invited as a Keynote Speaker in international conferences and summer schools and has been a Tutorial Lecturer at top-notch conferences in his area (e.g., CVPR, ECCV, ICPR, ACL, ECML). Prof. Pelillo is Fellow of the IEEE, the IAPR, and the AAIA, and is an IEEE SMC Distinguished Lecturer. His Erdös number is 2.
Martina Mattioli is a Ph.D. Student in the Department of Environmental Sciences, Informatics, and Statistics (DAIS) at the University of Ca' Foscari (Venice), under the supervision of Professor Marcello Pelillo. She is part of the Italian National Ph.D. Program in Artificial Intelligence for Industry 4.0., with Polytechnic of Turin as the leading university. She got a bachelor’s degree in Communication, Innovation, and Multimedia studies from the University of Pavia and a master's degree in Theory and Technology of Communication from the University of Milano-Bicocca. Her research interests lie at the intersection of epistemology and machine learning. Currently, she is dealing with the philosophical aspects of explanation. Her other research topics include the foundation of machine learning from the standpoint of the philosophy of science, and the philosophical aspects of similarity and categorization.
