8 citations · 8 across the 4 of their papers we have counts for
4 papers
Trust-free Personalized Decentralized Learning
Yawen Li, Yan Li, Junping Du +3
Personalized collaborative learning in federated settings faces a critical trade-off between customization and participant trust. Existing approaches typically rely on centralized…
Federated Topic Model and Model Pruning Based on Variational Autoencoder
Chengjie Ma, Yawen Li, Meiyu Liang +1
Topic modeling has emerged as a valuable tool for discovering patterns and topics within large collections of documents. However, when cross-analysis involves multiple parties, dat…
Recent Advances on Federated Learning: A Systematic Survey
Bingyan Liu, Nuoyan Lv, Yuanchun Guo +1
Federated learning has emerged as an effective paradigm to achieve privacy-preserving collaborative learning among different parties. Compared to traditional centralized learning t…
Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation
Guanhua Ye, Tong Chen, Yawen Li +3
In this paper, we propose a Similarity-Quality-based Messenger Distillation (SQMD) framework for heterogeneous asynchronous on-device healthcare analytics. By introducing a preload…