Xinwei Zhang - RankMe

33 papers A* 9C 1Misc 1Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. ICLR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. ICLR Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni
2024	J	`jnl`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. CoRR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2024	A*	`conf`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. ICML Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	J	`jnl`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. CoRR Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	—	`conf`	Building Large Models from Small Distributed Models: A Layer Matching Approach. SAM Xinwei Zhang, Bingqing Song, Mehrdad Honarkhah, Jie Ding, Mingyi Hong
2024	A*	`conf`	DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. NeurIPS Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn
2024	J	`jnl`	DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. CoRR Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn
2024	J	`jnl`	DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. CoRR Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni
2024	A*	`conf`	Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. ICLR Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong
2024	J	`jnl`	GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. Trans. Mach. Learn. Res. Xinwei Zhang, Mingyi Hong, Jie Chen
2024	J	`jnl`	Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation. Trans. Mach. Learn. Res. Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen
2024	A*	`conf`	Pre-training Differentially Private Models with Limited Public Data. NeurIPS Zhiqi Bu, Xinwei Zhang, Sheng Zha, Mingyi Hong, George Karypis
2024	J	`jnl`	Pre-training Differentially Private Models with Limited Public Data. CoRR Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis
2023	J	`jnl`	Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. CoRR Xinwei Zhang, Zhiqi Bu, Zhiwei Steven Wu, Mingyi Hong
2023	A*	`conf`	FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. ICML Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong
2023	J	`jnl`	GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. CoRR Xinwei Zhang, Mingyi Hong, Jie Chen
2023	J	`jnl`	Understanding a Class of Decentralized and Federated Optimization Algorithms: A Multirate Feedback Control Perspective. SIAM J. Optim. Xinwei Zhang, Mingyi Hong, Nicola Elia
2022	A*	`conf`	A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms. ICML Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Nicola Elia
2022	J	`jnl`	FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features. IEEE Trans. Signal Process. Yang Liu, Xinwei Zhang, Yan Kang, Liping Li, Tianjian Chen, Mingyi Hong, Qiang Yang
2022	J	`jnl`	Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective. CoRR Xinwei Zhang, Mingyi Hong, Nicola Elia
2022	A*	`conf`	Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi
2021	J	`jnl`	FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data. IEEE Trans. Signal Process. Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu
2021	J	`jnl`	Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi
2020	C	`conf`	A Sum-of-Squares Optimization Method for Learning and Controlling Photovoltaic Systems. ACC Xinwei Zhang, Victor Purba, Mingyi Hong, Sairaj V. Dhople
2020	J	`jnl`	Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond. CoRR Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu
2020	J	`jnl`	Distributed Learning in the Nonconvex World: From batch data to streaming and beyond. IEEE Signal Process. Mag. Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu
2020	J	`jnl`	FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data. CoRR Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu
2020	J	`jnl`	Hybrid Federated Learning: Algorithms and Implementation. CoRR Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen
2020	J	`jnl`	Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention. CoRR 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
2019	J	`jnl`	A Communication Efficient Vertical Federated Learning Framework. CoRR Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, Qiang Yang
2019	Misc	`conf`	DImplementing First-order Optimization Methods: Algorithmic Considerations and Bespoke Microcontrollers. ACSSC Xinwei Zhang, John Sartori, Mingyi Hong, Sairaj V. Dhople
2019	—	`conf`	GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization. DSW Songtao Lu, Xinwei Zhang, Haoran Sun, Mingyi Hong