most citedProvably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation

1 citations · 2 across the 4 of their papers we have counts for

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3 papers

cs.LG2022★ 1 cited

Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation

Jing Dong, Li Shen, Yinggan Xu +1

We study the convergence of the actor-critic algorithm with nonlinear function approximation under a nonconvex-nonconcave primal-dual formulation. Stochastic gradient descent ascen…

cs.LG2022

Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization

Canzhe Zhao, Yanjie Ze, Jing Dong +2

Temporal difference (TD) learning is a widely used method to evaluate policies in reinforcement learning. While many TD learning methods have been developed in recent years, little…

cs.LG2021

Cascading Bandit under Differential Privacy

Kun Wang, Jing Dong, Baoxiang Wang +2

This paper studies \emph{differential privacy (DP)} and \emph{local differential privacy (LDP)} in cascading bandits. Under DP, we propose an algorithm which guarantees -indisti…