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20232026
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cs.LG2026

GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning

Haitong Ma, Chenxiao Gao, Tianyi Chen +2

A commonly used family of RL algorithms for diffusion policies conducts softmax reweighting over samples from the behavior policy, which often induces an overgreedy policy and fail…

cs.LG2026

Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning

Bo Dai, Na Li, Dale Schuurmans

Self-supervised learning (SSL) has improved empirical performance by unleashing the power of unlabeled data for practical applications. Specifically, SSL extracts the representatio…

cs.LG2025

Max-Entropy Reinforcement Learning with Flow Matching and A Case Study on LQR

Yuyang Zhang, Yang Hu, Bo Dai +1

Soft actor-critic (SAC) is a popular algorithm for max-entropy reinforcement learning. In practice, the energy-based policies in SAC are often approximated using simple policy clas…

cs.LG2025

One-Step Flow Policy Mirror Descent

Tianyi Chen, Haitong Ma, Na Li +2

Diffusion policies have achieved great success in online reinforcement learning (RL) due to their strong expressive capacity. However, the inference of diffusion policy models reli…

cs.LG2025

Efficient Online Reinforcement Learning for Diffusion Policy

Haitong Ma, Tianyi Chen, Kai Wang +2

Diffusion policies have achieved superior performance in imitation learning and offline reinforcement learning (RL) due to their rich expressiveness. However, the conventional diff…

cs.LG2024

Primal-Dual Spectral Representation for Off-policy Evaluation

Yang Hu, Tianyi Chen, Na Li +2

Off-policy evaluation (OPE) is one of the most fundamental problems in reinforcement learning (RL) to estimate the expected long-term payoff of a given target policy with only expe…