CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity. - Pengyun Yue; Hanzhen Zhao; Cong Fang 001; Di He 001; Liwei Wang 001; Zhouchen Lin; Song-Chun Zhu (CoRR, 2023)

Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization. - Yuanshi Liu; Hanzhen Zhao; Yang Xu 055; Pengyun Yue; Cong Fang 001 (CoRR, 2023)

SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process. - Hanzhen Zhao; Xingyu Xie; Cong Fang 001; Zhouchen Lin (ICLR, 2025)

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression. - Shihong Ding; Haihan Zhang; Hanzhen Zhao; Cong Fang 001 (CoRR, 2025)