DImplementing First-order Optimization Methods: Algorithmic Considerations and Bespoke Microcontrollers. - Xinwei Zhang 001; John Sartori; Mingyi Hong 001; Sairaj V. Dhople (ACSSC, 2019)

GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization. - Songtao Lu; Xinwei Zhang 001; Haoran Sun; Mingyi Hong 001 (DSW, 2019)

A Communication Efficient Vertical Federated Learning Framework. - Yang Liu 165; Yan Kang 001; Xinwei Zhang 001; Liping Li 004; Yong Cheng; Tianjian Chen; Mingyi Hong 001; Qiang Yang 001 (CoRR, 2019)

A Sum-of-Squares Optimization Method for Learning and Controlling Photovoltaic Systems. - Xinwei Zhang 001; Victor Purba; Mingyi Hong 001; Sairaj V. Dhople (ACC, 2020)

Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond. - Tsung-Hui Chang; Mingyi Hong 001; Hoi-To Wai; Xinwei Zhang 001; Songtao Lu (CoRR, 2020)

FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data. - Xinwei Zhang 001; Mingyi Hong 001; Sairaj V. Dhople; Wotao Yin; Yang Liu 165 (CoRR, 2020)

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention. - Ce Ju; Ruihui Zhao; Jichao Sun; Xiguang Wei; Bo Zhao; Yang Liu 165; Hongshan Li; Tianjian Chen; Xinwei Zhang 001; Dashan Gao 002; Ben Tan; Han Yu 001; et al. (CoRR, 2020)

Hybrid Federated Learning: Algorithms and Implementation. - Xinwei Zhang 001; Wotao Yin; Mingyi Hong 001; Tianyi Chen (CoRR, 2020)

Distributed Learning in the Nonconvex World: From batch data to streaming and beyond. - Tsung-Hui Chang; Mingyi Hong 001; Hoi-To Wai; Xinwei Zhang 001; Songtao Lu (IEEE Signal Process. Mag., 2020)

FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data. - Xinwei Zhang 001; Mingyi Hong 001; Sairaj V. Dhople; Wotao Yin; Yang Liu 165 (IEEE Trans. Signal Process., 2021)

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. - Xinwei Zhang 001; Xiangyi Chen; Mingyi Hong 001; Steven Wu 001; Jinfeng Yi (ICML, 2022)

A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms. - Xinwei Zhang 001; Mingyi Hong 001; Sairaj V. Dhople; Nicola Elia (ICML, 2022)

Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective. - Xinwei Zhang 001; Mingyi Hong 001; Nicola Elia (CoRR, 2022)

FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features. - Yang Liu 165; Xinwei Zhang 001; Yan Kang 001; Liping Li 004; Tianjian Chen; Mingyi Hong 001; Qiang Yang 001 (IEEE Trans. Signal Process., 2022)

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. - Bingqing Song; Prashant Khanduri; Xinwei Zhang 001; Jinfeng Yi; Mingyi Hong 001 (ICML, 2023)

Understanding a Class of Decentralized and Federated Optimization Algorithms: A Multirate Feedback Control Perspective. - Xinwei Zhang 001; Mingyi Hong 001; Nicola Elia (SIAM J. Optim., 2023)

Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. - Xinwei Zhang 001; Zhiqi Bu; Steven Wu 001; Mingyi Hong 001 (ICLR, 2024)

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. - Yunsheng Tian; Ane Zuniga; Xinwei Zhang 001; Johannes P. Dürholt; Payel Das; Jie Chen 007; Wojciech Matusik; Mina Konakovic-Lukovic (ICML, 2024)

Building Large Models from Small Distributed Models: A Layer Matching Approach. - Xinwei Zhang 001; Bingqing Song; Mehrdad Honarkhah; Jie Ding 002; Mingyi Hong 001 (SAM, 2024)

DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. - Xinwei Zhang 001; Zhiqi Bu; Mingyi Hong 001; Meisam Razaviyayn (NeurIPS, 2024)

Pre-training Differentially Private Models with Limited Public Data. - Zhiqi Bu; Xinwei Zhang 001; Sheng Zha; Mingyi Hong 001; George Karypis (NeurIPS, 2024)

GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. - Xinwei Zhang 001; Mingyi Hong 001; Jie Chen 007 (Trans. Mach. Learn. Res., 2024)

Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation. - Xinwei Zhang 001; Wotao Yin; Mingyi Hong 001; Tianyi Chen (Trans. Mach. Learn. Res., 2024)

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. - Xinwei Zhang 001; Zhiqi Bu; Borja Balle; Mingyi Hong 001; Meisam Razaviyayn; Vahab Mirrokni (ICLR, 2025)

Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. - Zeman Li; Xinwei Zhang 001; Peilin Zhong; Yuan Deng; Meisam Razaviyayn; Vahab Mirrokni (ICLR, 2025)