4 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Feature Matching Data Synthesis for Non-IID Federated Learning
Zijian Li, Yuchang Sun, Jiawei Shao +3
Federated learning (FL) has emerged as a privacy-preserving paradigm that trains neural networks on edge devices without collecting data at a central server. However, FL encounters…
cs.LG2023★ 4 cited
pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning
Jiahao Tan, Yipeng Zhou, Gang Liu +2
The federated learning (FL) paradigm emerges to preserve data privacy during model training by only exposing clients' model parameters rather than original data. One of the biggest…