Xinwei Zhang

According to our database, Xinwei Zhang authored at least 26 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation.

Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen

Trans. Mach. Learn. Res., 2024

GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data.

Xinwei Zhang, Mingyi Hong, Jie Chen

Trans. Mach. Learn. Res., 2024

Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models.

Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni

CoRR, 2024

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction.

Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni

CoRR, 2024

DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction.

Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn

CoRR, 2024

Pre-training Differentially Private Models with Limited Public Data.

Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis

CoRR, 2024

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints.

Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic

CoRR, 2024

Building Large Models from Small Distributed Models: A Layer Matching Approach.

Xinwei Zhang, Bingqing Song, Mehrdad Honarkhah, Jie Dingl, Mingyi Hong

Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints.

Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic Lukovic

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach.

Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Understanding a Class of Decentralized and Federated Optimization Algorithms: A Multirate Feedback Control Perspective.

Xinwei Zhang, Mingyi Hong, Nicola Elia

SIAM J. Optim., 2023

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.

Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong

Proceedings of the International Conference on Machine Learning, 2023

2022

FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features.

Yang Liu, Xinwei Zhang, Yan Kang, Liping Li, Tianjian Chen, Mingyi Hong, Qiang Yang

IEEE Trans. Signal Process., 2022

Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective.

Xinwei Zhang, Mingyi Hong, Nicola Elia

CoRR, 2022

A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms.

Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Nicola Elia

Proceedings of the International Conference on Machine Learning, 2022

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy.

Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi

Proceedings of the International Conference on Machine Learning, 2022

2021

FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data.

Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu

IEEE Trans. Signal Process., 2021

2020

Distributed Learning in the Nonconvex World: From batch data to streaming and beyond.

Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu

IEEE Signal Process. Mag., 2020

Hybrid Federated Learning: Algorithms and Implementation.

Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen

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, Hongshan Li, Tianjian Chen, Xinwei Zhang, Dashan Gao, Ben Tan, Han Yu, Yuan Jin

CoRR, 2020

FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data.

Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu

CoRR, 2020

Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond.

Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu

CoRR, 2020

A Sum-of-Squares Optimization Method for Learning and Controlling Photovoltaic Systems.

Xinwei Zhang, Victor Purba, Mingyi Hong, Sairaj V. Dhople

Proceedings of the 2020 American Control Conference, 2020

2019

A Communication Efficient Vertical Federated Learning Framework.

Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, Qiang Yang

CoRR, 2019

GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization.

Songtao Lu, Xinwei Zhang, Haoran Sun, Mingyi Hong

Proceedings of the IEEE Data Science Workshop, 2019

DImplementing First-order Optimization Methods: Algorithmic Considerations and Bespoke Microcontrollers.

Xinwei Zhang, John Sartori, Mingyi Hong, Sairaj V. Dhople

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019