Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning
Baraa Bilbeisi, Mengchen Fan, Baocheng Geng +1
Conventional federated learning (FL) relies on parameter averaging, which forces clients to be doubly homogeneous: it demands an identical architecture and degrades under non-IID d…
cs.LG2025
PFedDST: Personalized Federated Learning with Decentralized Selection Training
Mengchen Fan, Keren Li, Tianyun Zhang +2
Distributed Learning (DL) enables the training of machine learning models across multiple devices, yet it faces challenges like non-IID data distributions and device capability dis…
cs.LG2024
Interpretable Data Fusion for Distributed Learning: A Representative Approach via Gradient Matching
Mengchen Fan, Baocheng Geng, Keren Li +2
This paper introduces a representative-based approach for distributed learning that transforms multiple raw data points into a virtual representation. Unlike traditional distribute…