9 citations · 10 across the 6 of their papers we have counts for
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cs.LG2025
Breaking Privacy in Federated Clustering: Perfect Input Reconstruction via Temporal Correlations
Guang Yang, Lixia Luo, Qiongxiu Li
Federated clustering allows multiple parties to discover patterns in distributed data without sharing raw samples. To reduce overhead, many protocols disclose intermediate centroid…
cs.LG2021★ 9 cited
RingFed: Reducing Communication Costs in Federated Learning on Non-IID Data
Guang Yang, Ke Mu, Chunhe Song +2
Federated learning is a widely used distributed deep learning framework that protects the privacy of each client by exchanging model parameters rather than raw data. However, feder…