activity
20122026
most citedHuman Activity Recognition using Recurrent Neural Networks

188 citations · 880 across the 70 of their papers we have counts for

collaborators
Showing 2020 · cs.LGShow all

7 papers · 2 filters

cs.LG2020★ 8 cited

Self-Imitation Advantage Learning

Johan Ferret, Olivier Pietquin, Matthieu Geist

Self-imitation learning is a Reinforcement Learning (RL) method that encourages actions whose returns were higher than expected, which helps in hard exploration and sparse reward p…

cs.LG2020★ 37 cited

Munchausen Reinforcement Learning

Nino Vieillard, Olivier Pietquin, Matthieu Geist

Bootstrapping is a core mechanism in Reinforcement Learning (RL). Most algorithms, based on temporal differences, replace the true value of a transiting state by their current esti…

cs.LG2020★ 107 cited

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk +9

In recent years, on-policy reinforcement learning (RL) has been successfully applied to many different continuous control tasks. While RL algorithms are often conceptually simple,…

cs.LG2020★ 4 cited

Show me the Way: Intrinsic Motivation from Demonstrations

Léonard Hussenot, Robert Dadashi, Matthieu Geist +1

The study of exploration in the domain of decision making has a long history but remains actively debated. From the vast literature that addressed this topic for decades under vari…

cs.LG2020★ 38 cited

Primal Wasserstein Imitation Learning

Robert Dadashi, Léonard Hussenot, Matthieu Geist +1

Imitation Learning (IL) methods seek to match the behavior of an agent with that of an expert. In the present work, we propose a new IL method based on a conceptually simple algori…

cs.LG2020

Stable and Efficient Policy Evaluation

Daoming Lyu, Bo Liu, Matthieu Geist +3

Policy evaluation algorithms are essential to reinforcement learning due to their ability to predict the performance of a policy. However, there are two long-standing issues lying…