Author

Matthieu Jonckheere

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#reinforcement learning Open access Oct 2026

When Optimization Forgets the Minority: Bias Amplification in Policy-Gradient Reinforcement Learning

Bias amplification, the tendency of trained models to be more biased than the data that produced them, is well documented in supervised learning. We study it in policy-gradient reinforcement learning, where there is no static dataset: each episode belongs to a latent group that shapes the reward but is invisible to the...

Juan Ignacio Fiore, Matthieu Jonckheere · Zenodo (CERN European Organi... · 0 citations

#reinforcement learning Aug 2026

When to Parallelize Stochastic Exploration of Rare Rewards in Reinforcement Learning

International audience

Ernesto García, Daniel Mastropietro, Paola Bermolen et al. · HAL (Le Centre pour la Commu... · 0 citations