3 papers
cs.LG2026
SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration
Kaustubh Mani, Yann Pequignot, Vincent Mai +1
Safe exploration is a prerequisite for deploying reinforcement learning (RL) agents in safety-critical domains. In this paper, we approach safe exploration through the lens of epis…
cs.LG2025
A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategy
Maxime Heuillet, Rishika Bhagwatkar, Jonas Ngnawé +6
Deep learning models operating in the image domain are vulnerable to small input perturbations. For years, robustness to such perturbations was pursued by training models from scra…
stat.ML2024
Improving Out-of-Distribution Detection by Combining Existing Post-hoc Methods
Paul Novello, Yannick Prudent, Joseba Dalmau +2
Since the seminal paper of Hendrycks et al. arXiv:1610.02136, Post-hoc deep Out-of-Distribution (OOD) detection has expanded rapidly. As a result, practitioners working on safety-c…