A Homogenization Approach for Gradient-Dominated Stochastic Optimization

no code implementations • 21 Aug 2023 • Jiyuan Tan, Chenyu Xue, Chuwen Zhang, Qi Deng, Dongdong Ge, Yinyu Ye

In this paper, we propose the stochastic homogeneous second-order descent method (SHSODM) for stochastic functions enjoying gradient dominance property based on a recently proposed homogenization approach.

Management Reinforcement Learning (RL) +2

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets

no code implementations • 15 Feb 2022 • Han Zhong, Wei Xiong, Jiyuan Tan, LiWei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

When the dataset does not have uniform coverage over all policy pairs, finding an approximate NE involves challenges in three aspects: (i) distributional shift between the behavior policy and the optimal policy, (ii) function approximation to handle large state space, and (iii) minimax optimization for equilibrium solving.