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math.OC2025
A Unified Zeroth-Order Optimization Framework via Oblivious Randomized Sketching
Haishan Ye, Xiangyu Chang, Xi Chen
We propose a new framework for analyzing zeroth-order optimization (ZOO) from the perspective of \emph{oblivious randomized sketching}.In this framework, commonly used gradient est…
math.OC2025
Can a One-Point Feedback Zeroth-order Algorithm Achieve Linear Dimension Dependent Sample Complexity?
Haishan Ye, Xiangyu Chang
We revisit the one-point feedback zeroth-order (ZO) optimization problem, a classical setting in derivative-free optimization where only a single noisy function evaluation is avail…
math.OC2024
Optimal Decentralized Composite Optimization for Convex Functions
Haishan Ye, Xiangyu Chang
In this paper, we focus on the decentralized composite optimization for convex functions. Because of advantages such as robust to the network and no communication bottle-neck in th…