Diagonal Preconditioning: Theory and Algorithms. - Zhaonan Qu; Yinyu Ye 001; Zhengyuan Zhou (CoRR, 2020)

Federated Learning's Blessing: FedAvg has Linear Speedup. - Zhaonan Qu; Kaixiang Lin; Jayant Kalagnanam; Zhaojian Li; Jiayu Zhou; Zhengyuan Zhou (CoRR, 2020)

Optimal Diagonal Preconditioning: Theory and Practice. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (CoRR, 2022)

On Sinkhorn's Algorithm and Choice Modeling. - Zhaonan Qu; Alfred Galichon; Johan Ugander (CoRR, 2023)

Scalable Approximate Optimal Diagonal Preconditioning. - Wenzhi Gao; Zhaonan Qu; Madeleine Udell; Yinyu Ye 001 (CoRR, 2023)

A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg. - Zhaonan Qu; Kaixiang Lin; Zhaojian Li; Jiayu Zhou; Zhengyuan Zhou (J. Artif. Intell. Res., 2023)

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting. - Serina Chang; Frederic Koehler; Zhaonan Qu; Jure Leskovec; Johan Ugander (ICML, 2024)

Optimal Diagonal Preconditioning. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (Oper. Res., 2025)