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Erwan Le Pennec

3 accepted papers

2024

Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms

Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist
NeurIPS 2024poster

To address the challenges of sim-to-real gap and sample efficiency in reinforcement learning (RL), this work studies distributionally robust Markov decision processes (RMDPs) --- optimize the worst-case performance when the deployed environment is within an uncertainty set around some nominal MDP. D…

Cited by 0Source ↗PDF ↗Scholar ↗
2023

Input uncertainty propagation through trained neural networks

Paul Monchot, Loic Coquelin, Sébastien Julien Petit, Sébastien Marmin, Erwan Le Pennec, Nicolas Fischer
ICML 2023poster

When physical sensors are involved, such as image sensors, the uncertainty over the input data is often a major component of the output uncertainty of machine learning models. In this work, we address the problem of input uncertainty propagation through trained neural networks. We do not rely on a G…

Cited by 2Source ↗PDF ↗Scholar ↗