NIPS Proceedings
β
Books
Zhaoran Wang
10 Papers
Convergent Policy Optimization for Safe Reinforcement Learning
(2019)
Neural Temporal-Difference Learning Converges to Global Optima
(2019)
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy
(2019)
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
(2019)
Statistical-Computational Tradeoff in Single Index Models
(2019)
Variance Reduced Policy Evaluation with Smooth Function Approximation
(2019)
Contrastive Learning from Pairwise Measurements
(2018)
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
(2018)
Provable Gaussian Embedding with One Observation
(2018)
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma
(2017)