The development of Machine Learning (ML) and Artificial Intelligence (AI) metlhods and algorithms raises questions from various scientific fields with computer science and mathematics in front line.

According to the intended purpose (reasoning and problem solving, knowledge representation, planning, learning, motion, natural language processing, perception or emergent intelligence ?), the targeted domain of application and the nature of the available data, the mathematical foundations of ML and AI encompass many distinct areas such as calculus, probability, statistics, algebra, optimization, but also geometry, graph theory, computational complexity, or game theory for instance.

The semester organized by the Centre Henri Lebesgue aims at giving an overview of the mathematical concepts/knowledge of the mostly used methods and algorithms in ML and AI, including deep learning ones. The foreseen events are designed to respect a balance between methodology and theory, and to address a large public, from young and senior researchers to business professionals who are willing to open the black box. 

Scientific coordination: Magalie Fromont