3 papers
cs.LG2026
RefProtoFL: Communication-Efficient Federated Learning via External-Referenced Prototype Alignment
Hongyue Wu, Hangyu Li, Guodong Fan +3
Federated learning (FL) enables collaborative model training without sharing raw data in edge environments, but is constrained by limited communication bandwidth and heterogeneous…
cs.LG2025
Efficient Federated Learning with Encrypted Data Sharing for Data-Heterogeneous Edge Devices
Hangyu Li, Hongyue Wu, Guodong Fan +3
As privacy protection gains increasing importance, more models are being trained on edge devices and subsequently merged into the central server through Federated Learning (FL). Ho…
cs.GT2024
FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms
Guoli Wu, Zhiyong Feng, Shizhan Chen +6
Traditional recommendation systems focus on maximizing user satisfaction by suggesting their favourite items. This user-centric approach may lead to unfair exposure distribution am…