ClusterGrad: Adaptive Gradient Compression by Clustering in Federated Learning. - Laizhong Cui; Xiaoxin Su; Yipeng Zhou; Lei Zhang 066 (GLOBECOM, 2020)

Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates. - Laizhong Cui; Xiaoxin Su; Yipeng Zhou; Yi Pan 001 (IEEE J. Sel. Areas Commun., 2021)

Optimal Rate Adaption in Federated Learning with Compressed Communications. - Laizhong Cui; Xiaoxin Su; Yipeng Zhou; Jiangchuan Liu (INFOCOM, 2022)

CREAT: Blockchain-Assisted Compression Algorithm of Federated Learning for Content Caching in Edge Computing. - Laizhong Cui; Xiaoxin Su; Zhongxing Ming; Ziteng Chen; Shu Yang 002; Yipeng Zhou; Wei Xiao (IEEE Internet Things J., 2022)

A Fast Blockchain-Based Federated Learning Framework With Compressed Communications. - Laizhong Cui; Xiaoxin Su; Yipeng Zhou (IEEE J. Sel. Areas Commun., 2022)

On Model Transmission Strategies in Federated Learning With Lossy Communications. - Xiaoxin Su; Yipeng Zhou; Laizhong Cui; Jiangchuan Liu (IEEE Trans. Parallel Distributed Syst., 2023)

Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression. - Xiaoxin Su; Yipeng Zhou; Laizhong Cui; Song Guo 001 (INFOCOM, 2024)

Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes. - Xiaoxin Su; Yipeng Zhou; Laizhong Cui; John C. S. Lui; Jiangchuan Liu (INFOCOM, 2024)

Fast-Convergent Wireless Federated Learning: A Voting-Based TopK Model Compression Approach. - Xiaoxin Su; Yipeng Zhou; Laizhong Cui; Quan Z. Sheng; Yinggui Wang; Song Guo 001 (IEEE J. Sel. Areas Commun., 2024)

Two-dimensional cutting stock problem with flexible length and usable leftovers in the steel industry. - Yunfeng Ma; Jiayi Zhang; Xijie Yang; Jihao Li; Xiaoxin Su; Haoxun Chen (Eur. J. Oper. Res., 2025)