Edge-Assisted Hierarchical Federated Learning with Non-IID Data. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled Ben Letaief (CoRR, 2019)

Client-Edge-Cloud Hierarchical Federated Learning. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (ICC, 2020)

Hierarchical Quantized Federated Learning: Convergence Analysis and System Design. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (CoRR, 2021)

Communication-Efficient Federated Distillation with Active Data Sampling. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (ICC, 2022)

Binary Federated Learning with Client-Level Differential Privacy. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (GLOBECOM, 2023)

A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency. - Jiawei Shao; Zijian Li 023; Wenqiang Sun; Tailin Zhou; Yuchang Sun 001; Lumin Liu; Zehong Lin; Jun Zhang 004 (CoRR, 2023)

Hierarchical Federated Learning With Quantization: Convergence Analysis and System Design. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (IEEE Trans. Wirel. Commun., 2023)

Quantization and Privacy Noise Co-Design for Utility-Privacy-Communication Trade-off in Federated Learning. - Lumin Liu; Yuyi Mao; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (GLOBECOM, 2024)

The Effect of Quantization in Federated Learning:A Rényi Differential Privacy Perspective. - Tianqu Kang; Lumin Liu; Hengtao He; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (MeditCom, 2024)

The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective. - Tianqu Kang; Lumin Liu; Hengtao He; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (CoRR, 2024)

Communication-Efficient Federated Distillation: Theoretical Analysis and Performance Enhancement. - Lumin Liu; Jun Zhang 004; Shenghui Song 001; Khaled B. Letaief (IEEE Internet Things J., 2024)