Yu Zhang

activity

20192022

most citedCUP: A Conservative Update Policy Algorithm for Safe Reinforcement Learning

7 citations · 9 across the 5 of their papers we have counts for

collaborators

Showing 2019Show all

3 papers · 1 filter

cs.LG2019

Gradient Q $(σ, λ)$ : A Unified Algorithm with Function Approximation for Reinforcement Learning

Long Yang, Yu Zhang, Qian Zheng +2

Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sarsa) algorithms are efficient and frequently used techniques in reinforcement learning. Q $(σ, λ)$ is the firs…

cs.LG2019

Expected Sarsa( $λ$ ) with Control Variate for Variance Reduction

Long Yang, Yu Zhang, Jun Wen +3

Off-policy learning is powerful for reinforcement learning. However, the high variance of off-policy evaluation is a critical challenge, which causes off-policy learning falls into…

cs.LG2019★ 2 cited

Policy Optimization with Stochastic Mirror Descent

Long Yang, Yu Zhang, Gang Zheng +5

Improving sample efficiency has been a longstanding goal in reinforcement learning. This paper proposes $VRMPO$ algorithm: a sample efficient policy gradient method with s…

Gradient Q(σ,λ): A Unified Algorithm with Function Approximation for Reinforcement Learning

Expected Sarsa(λ) with Control Variate for Variance Reduction

Policy Optimization with Stochastic Mirror Descent

Gradient Q $(σ, λ)$ : A Unified Algorithm with Function Approximation for Reinforcement Learning

Expected Sarsa( $λ$ ) with Control Variate for Variance Reduction