Yann Ollivier

Paris, France

After receiving a Ph.D. in probability and group theory, Yann joined the CNRS, the French national research institute. He initially worked on unveiling connections between probability, Markov chains, differential geometry, and discrete geometry. For this work, he was awarded the bronze medal of the CNRS. Due to a lifelong interest in artificial intelligence, Yann focused his research on machine learning and joined the computer science department at Paris-Sud University. Following the industrial development of deep learning, he joined Facebook AI Research. Yann works on understanding and improving the learning algorithms for neural networks. In the long term, he is interested in building general artificial intelligence systems. More specific fields of interest include the geometry of gradient descent algorithms, the dynamics of recurrent networks and online learning, better algorithms for reinforcement learning, and what "learning" means in terms of information theory.

Yann's Publications

June 10, 2019

RESEARCH

ML APPLICATIONS

Separating value functions across time-scales

Joshua Romoff, Peter Henderson, Ahmed Touati, Emma Brunskill, Joelle Pineau, Yann Ollivier,

June 10, 2019

June 10, 2019

RESEARCH

RANKING & RECOMMENDATIONS

Making Deep Q-learning Methods Robust to Time Discretization

Corentin Tallec, Léonard Blier, Yann Ollivier,

June 10, 2019

June 09, 2019

RESEARCH

THEORY

First-order Adversarial Vulnerability of Neural Networks and Input Dimension

Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Scholkopf, Leon Bottou, David Lopez-Paz,

June 09, 2019