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math.OC2024
Landscape of Policy Optimization for Finite Horizon MDPs with General State and Action
Xin Chen, Yifan Hu, Minda Zhao
Policy gradient methods are widely used in reinforcement learning. Yet, the nonconvexity of policy optimization poses significant challenges in understanding the global convergence…
math.OC2024
Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles
Yifan Hu, Jie Wang, Xin Chen +1
We consider stochastic optimization when one only has access to biased stochastic oracles of the objective and the gradient, and obtaining stochastic gradients with low biases come…
math.OC2024
Tensor Completion via Integer Optimization
Xin Chen, Sukanya Kudva, Yongzheng Dai +2
The main challenge with the tensor completion problem is a fundamental tension between computation power and the information-theoretic sample complexity rate. Past approaches eithe…