11 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data
Yiyue Chen, Usman Akram, Chianing Wang +1
Motivated by the high resource costs and privacy concerns associated with centralized machine learning, federated learning (FL) has emerged as an efficient alternative that enables…
cs.LG2023
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity
Yiyue Chen, Haris Vikalo, Chianing Wang
Motivated by high resource costs of centralized machine learning schemes as well as data privacy concerns, federated learning (FL) emerged as an efficient alternative that relies o…
cs.LG2023★ 11 cited
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation
Huancheng Chen, Johnny, Wang +1
Heterogeneity of data distributed across clients limits the performance of global models trained through federated learning, especially in the settings with highly imbalanced class…