most citedDual-Distilled Heterogeneous Federated Learning with Adaptive Margins for Trainable Global Prototypes

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2025★ 1 cited

Dual-Distilled Heterogeneous Federated Learning with Adaptive Margins for Trainable Global Prototypes

Fatema Siddika, Md Anwar Hossen, Wensheng Zhang +3

Heterogeneous Federated Learning (HFL) has gained significant attention for its capacity to handle both model and data heterogeneity across clients. Prototype-based HFL methods eme…

cs.GT2024

Fair Allocation of Bandwidth At Edge Servers For Concurrent Hierarchical Federated Learning

Md Anwar Hossen, Fatema Siddika, Wensheng Zhang

This paper explores concurrent FL processes within a three-tier system, with edge servers between edge devices and FL servers. A challenge in this setup is the limited bandwidth fr…