Yann Ollivier

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 35

Top Topics

Learning Models

Temporal Difference

Reinforcement Learning

Top Venues

Publications

Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier
Fast Imitation via Behavior Foundation Models. ICLR (2024)
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
Simple Ingredients for Offline Reinforcement Learning. CoRR (2024)
Ahmed Touati, Jérémy Rapin, Yann Ollivier
Does Zero-Shot Reinforcement Learning Exist? ICLR (2023)
Ahmed Touati, Jérémy Rapin, Yann Ollivier
Does Zero-Shot Reinforcement Learning Exist? CoRR (2022)
Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier
Agnostic Physics-Driven Deep Learning. CoRR (2022)
Ahmed Touati, Yann Ollivier
Learning One Representation to Optimize All Rewards. CoRR (2021)
Ahmed Touati, Yann Ollivier
Learning One Representation to Optimize All Rewards. NeurIPS (2021)
Léonard Blier, Yann Ollivier
Unbiased Methods for Multi-Goal Reinforcement Learning. CoRR (2021)
Léonard Blier, Corentin Tallec, Yann Ollivier
Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint. CoRR (2021)
Pierre Wolinski, Guillaume Charpiat, Yann Ollivier
Interpreting a Penalty as the Influence of a Bayesian Prior. CoRR (2020)
Carl-Johann Simon-Gabriel, Yann Ollivier, Léon Bottou, Bernhard Schölkopf, David Lopez-Paz
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. ICML (2019)
Corentin Tallec, Léonard Blier, Yann Ollivier
Making Deep Q-learning methods robust to time discretization. CoRR (2019)
Corentin Tallec, Léonard Blier, Yann Ollivier
Making Deep Q-learning methods robust to time discretization. ICML (2019)
Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Yann Ollivier, Hervé Jégou
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference. ICML (2019)
Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau
Separating value functions across time-scales. CoRR (2019)
Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill
Separable value functions across time-scales. ICML (2019)
Léonard Blier, Pierre Wolinski, Yann Ollivier
Learning with Random Learning Rates. ECML/PKDD (2) (2019)
Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier, Cordelia Schmid, Hervé Jégou
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference. CoRR (2019)
Léonard Blier, Yann Ollivier
Do Deep Learning Models Have Too Many Parameters? An Information Theory Viewpoint. CoRR (2018)
Léonard Blier, Pierre Wolinski, Yann Ollivier
Learning with Random Learning Rates. CoRR (2018)
Corentin Tallec, Yann Ollivier
Can recurrent neural networks warp time? ICLR (Poster) (2018)
Thomas Lucas, Corentin Tallec, Jakob Verbeek, Yann Ollivier
Mixed batches and symmetric discriminators for GAN training. CoRR (2018)
Thomas Lucas, Corentin Tallec, Yann Ollivier, Jakob Verbeek
Mixed batches and symmetric discriminators for GAN training. ICML (2018)
Corentin Tallec, Yann Ollivier
Can recurrent neural networks warp time? CoRR (2018)
Léonard Blier, Yann Ollivier
The Description Length of Deep Learning models. NeurIPS (2018)
Yann Ollivier
Approximate Temporal Difference Learning is a Gradient Descent for Reversible Policies. CoRR (2018)
Corentin Tallec, Yann Ollivier
Unbiased Online Recurrent Optimization. ICLR (Poster) (2018)
Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Schölkopf, Léon Bottou, David Lopez-Paz
Adversarial Vulnerability of Neural Networks Increases With Input Dimension. CoRR (2018)
Gaétan Marceau-Caron, Yann Ollivier
Natural Langevin Dynamics for Neural Networks. GSI (2017)
Yann Ollivier, Ludovic Arnold, Anne Auger, Nikolaus Hansen
Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. J. Mach. Learn. Res. 18 (2017)
Corentin Tallec, Yann Ollivier
Unbiasing Truncated Backpropagation Through Time. CoRR (2017)
Yann Ollivier
True Asymptotic Natural Gradient Optimization. CoRR (2017)
Corentin Tallec, Yann Ollivier
Unbiased Online Recurrent Optimization. CoRR (2017)
Gaétan Marceau-Caron, Yann Ollivier
Natural Langevin Dynamics for Neural Networks. CoRR (2017)
Gaétan Marceau-Caron, Yann Ollivier
Practical Riemannian Neural Networks. CoRR (2016)
Yann Ollivier
Laplace's rule of succession in information geometry. CoRR (2015)
Pierre-Yves Massé, Yann Ollivier
Speed learning on the fly. CoRR (2015)
Yann Ollivier, Guillaume Charpiat
Training recurrent networks online without backtracking. CoRR (2015)
Yann Ollivier
Laplace's Rule of Succession in Information Geometry. GSI (2015)
Yann Ollivier
Auto-encoders: reconstruction versus compression. CoRR (2014)
Yann Ollivier
Persistent Contextual Neural Networks for learning symbolic data sequences. CoRR (2013)
Yann Ollivier
Information-Geometric Optimization: The Interest of Information Theory for Discrete and Continuous Optimization. GSI (2013)
Yann Ollivier
Riemannian metrics for neural networks CoRR (2013)
Youhei Akimoto, Yann Ollivier
Objective improvement in information-geometric optimization. FOGA (2013)
Yann Ollivier, Cédric Villani
A Curved Brunn-Minkowski Inequality on the Discrete Hypercube, Or: What Is the Ricci Curvature of the Discrete Hypercube? SIAM J. Discret. Math. 26 (3) (2012)
Youhei Akimoto, Yann Ollivier
Objective Improvement in Information-Geometric Optimization CoRR (2012)
Ludovic Arnold, Yann Ollivier
Layer-wise learning of deep generative models CoRR (2012)
Yann Ollivier, Pierre Senellart
Finding Related Pages Using Green Measures: An Illustration with Wikipedia. AAAI (2007)
Yann Ollivier
Some Small Cancellation Properties of Random Groups. Int. J. Algebra Comput. 17 (1) (2007)
Yann Ollivier
Rate of convergence of crossover operators. Random Struct. Algorithms 23 (1) (2003)