Séminaire de Lionel Jouffe, cofondateur de Bayesia S.A.S.


Date: 26/03/2019
Heure: 10h30
Lieu: CERIUM, IUT de Laval
Intervenant: Lionel Jouffe, cofondateur de Bayesia S.A.S.


Bio : Dr. Lionel Jouffe is co-founder and CEO of France-based Bayesia S.A.S. Lionel holds a Ph.D. in Computer Science from the University of Rennes and has been working in the field of Artificial Intelligence since the early 1990s. While working as a Professor/Researcher at ESIEA, Lionel started exploring the potential of Bayesian networks. After co-founding Bayesia in 2001, he and his team have been working full-time on the development BayesiaLab, which has since emerged as the leading software package for knowledge discovery, data mining and knowledge modeling using Bayesian networks. BayesiaLab enjoys broad acceptance in academic communities as well as in business and industry.


Résumé : The theoretical framework of the Bayesian Network (BN) is one of the main pillars of Artificial Intelligence. It provides an elegant and robust approach for manually building machine learning models that represent the field studied in a holistic way, while taking into account uncertainty. These models allow carrying out rigorous probabilistic inference, by propagating pieces of evidence that have been gathered on a subset of variables on the remaining variables. Over the last 25 years, BNs have emerged as a practically feasible form of expert knowledge representation and as a new comprehensive data analysis framework. With the ever-increasing computing power, their computational efficiency and inherently visual structure make them attractive for exploring and explaining complex problems. BNs are now a powerful tool for deep understanding of very complex and high-dimensional problem domains. Deep understanding means knowing, not merely how things behaved yesterday, but also how things will behave under new hypothetical circumstances tomorrow. More specifically, a BN allows explicit reasoning, and deliberate reasoning to allow the anticipation of the consequences of actions that have not yet be taken.

Vidéo accessible pour les membres de Le Mans Université.