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cs.LG2025
Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
Shaocong Ma, Heng Huang
In this paper, we explore the two-point zeroth-order gradient estimator and identify the distribution of random perturbations that minimizes the estimator's asymptotic variance as…
cs.LG2025
Rectified Robust Policy Optimization for Model-Uncertain Constrained Reinforcement Learning without Strong Duality
Shaocong Ma, Ziyi Chen, Yi Zhou +1
The goal of robust constrained reinforcement learning (RL) is to optimize an agent's performance under the worst-case model uncertainty while satisfying safety or resource constrai…