7 papers
Rollback-Free Stable Brick Structures Generation
Chenhui Xu, Ziyue Bai, Fuxun Yu +2
While autoregressive models have advanced 3D generation, creating physically stable brick structures remains a challenge due to the strict requirements of gravity and interconnecti…
Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds
Shaocong Ma, Heng Huang
In this paper, we study Riemannian zeroth-order optimization in settings where the underlying Riemannian metric is geodesically incomplete, and the goal is to approximate stati…
Robust Reinforcement Learning in Finance: Modeling Market Impact with Elliptic Uncertainty Sets
Shaocong Ma, Heng Huang
In financial applications, reinforcement learning (RL) agents are commonly trained on historical data, where their actions do not influence prices. However, during deployment, thes…
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…
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
Shaocong Ma, Heng Huang
Zeroth-order optimization (ZOO) is an important framework for stochastic optimization when gradients are unavailable or expensive to compute. A potential limitation of existing ZOO…
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…