3 papers
cs.LG2026
Switching Successor Measures for Hierarchical Zero-shot Reinforcement Learning
Stefan Stojanovic, Alexandre Proutiere
Hierarchical reinforcement learning can improve generalization by decomposing long-horizon decision-making into simpler subproblems. However, existing approaches often rely on rest…
cs.LG2025
Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning
Bastien Dubail, Stefan Stojanovic, Alexandre Proutière
Low-rank structure is a common implicit assumption in many modern reinforcement learning (RL) algorithms. For instance, reward-free and goal-conditioned RL methods often presume th…
cs.LG2024
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
Stefan Stojanovic, Yassir Jedra, Alexandre Proutiere
We consider the problem of learning an -optimal policy in controlled dynamical systems with low-rank latent structure. For this problem, we present LoRa-PI (Low-Rank P…