2025

LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation

Li Ding*, Hao Zhang*, Wenrui Dai, Chenglin Li, Weijia Lu, ZHIFEI YANG, xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2025

LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation

Li Ding*, Hao Zhang*, Wenrui Dai, Chenglin Li, Weijia Lu, ZHIFEI YANG, xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2025

FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model Updates

Li Ding*, Hao Zhang*, Wenrui Dai, Chenglin Li, Weijia Lu, ZHIFEI YANG, xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2025

FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model Updates

Li Ding*, Hao Zhang*, Wenrui Dai, Chenglin Li, Weijia Lu, ZHIFEI YANG, xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2025

2024

Federated Learning Based on Model Discrepancy and Variance Reduction
Federated Learning Based on Model Discrepancy and Variance Reduction

Hao Zhang, Chenglin Li, Wenrui Dai, Ziyang Zheng, Junni Zou, Hongkai Xiong

IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2024

[Code] [Paper]

Federated Learning Based on Model Discrepancy and Variance Reduction

Hao Zhang, Chenglin Li, Wenrui Dai, Ziyang Zheng, Junni Zou, Hongkai Xiong

IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2024

[Code] [Paper]

Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach

Hao Zhang, Chenglin Li, Nuowen Kan, Ziyang Zheng, Wenrui Dai, Junni Zou, Hongkai Xiong

Neural Information Processing Systems (NeurIPS) 2024

[Code] [Paper]

Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach

Hao Zhang, Chenglin Li, Nuowen Kan, Ziyang Zheng, Wenrui Dai, Junni Zou, Hongkai Xiong

Neural Information Processing Systems (NeurIPS) 2024

[Code] [Paper]

Stabilizing and Accelerating Federated Learning on Heterogeneous Data with Partial Client Participation
Stabilizing and Accelerating Federated Learning on Heterogeneous Data with Partial Client Participation

Hao Zhang, Chenglin Li, Wenrui Dai, Ziyang Zheng, Junni Zou, Hongkai Xiong

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024

[Code] [Paper]

Stabilizing and Accelerating Federated Learning on Heterogeneous Data with Partial Client Participation

Hao Zhang, Chenglin Li, Wenrui Dai, Ziyang Zheng, Junni Zou, Hongkai Xiong

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024

[Code] [Paper]

2023

FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization

Hao Zhang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2023

[Code] [Paper]

FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization

Hao Zhang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong

International Conference on Machine Learning (ICML) 2023

[Code] [Paper]