8 papers · 1 filter
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…
Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces
Haitong Ma, Ofir Nabati, Aviv Rosenberg +7
Reinforcement learning (RL) struggles to scale to large, combinatorial action spaces common in many real-world problems. This paper introduces a novel framework for training discre…
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…
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…
Distributed Thompson sampling under constrained communication
Saba Zerefa, Zhaolin Ren, Haitong Ma +1
In Bayesian optimization, a black-box function is maximized via the use of a surrogate model. We apply distributed Thompson sampling, using a Gaussian process as a surrogate model,…
Efficient Duple Perturbation Robustness in Low-rank MDPs
Yang Hu, Haitong Ma, Bo Dai +1
The pursuit of robustness has recently been a popular topic in reinforcement learning (RL) research, yet the existing methods generally suffer from efficiency issues that obstruct…
Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
Haitong Ma, Zhaolin Ren, Bo Dai +1
We study sim-to-real skill transfer and discovery in the context of robotics control using representation learning. We draw inspiration from spectral decomposition of Markov decisi…
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
Zhaolin Ren, Tongzheng Ren, Haitong Ma +2
This paper proposes an approach, Spectral Dynamics Embedding Control (SDEC), to optimal control for nonlinear stochastic systems. This method reveals an infinite-dimensional featur…