most citedNatural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

math.OC2024

Accelerated Multi-Time-Scale Stochastic Approximation: Optimal Complexity and Applications in Reinforcement Learning and Multi-Agent Games

Sihan Zeng, Thinh T. Doan

Multi-time-scale stochastic approximation is an iterative algorithm for finding the fixed point of a set of coupled operators given their noisy samples. It has been observed th…

math.OC2024★ 1 cited

Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning

Sihan Zeng, Thinh T. Doan, Justin Romberg

Multi-task reinforcement learning (RL) aims to find a single policy that effectively solves multiple tasks at the same time. This paper presents a constrained formulation for multi…

cs.LG2019

Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables

Shaojie Xu, Sihan Zeng, Justin Romberg

Deep learning models have significantly improved the visual quality and accuracy on compressive sensing recovery. In this paper, we propose an algorithm for signal reconstruction f…