26 citations · 27 across the 9 of their papers we have counts for
4 papers · 1 filter
Robust Federated Fine-Tuning in Heterogeneous Networks with Unreliable Connections: An Aggregation View
Yanmeng Wang, Zhiwen Dai, Shuai Wang +4
Federated Fine-Tuning (FFT) has attracted growing interest as it leverages both server- and client-side data to enhance global model generalization while preserving privacy, and si…
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks
Shuai Wang, Yanqing Xu, Chaoqun You +2
Federated learning (FL) has been recognized as a viable solution for local-privacy-aware collaborative model training in wireless edge networks, but its practical deployment is hin…
Towards Fast Personalized Semi-Supervised Federated Learning in Edge Networks: Algorithm Design and Theoretical Guarantee
Shuai Wang, Yanqing Xu, Yanyi Yuan +1
Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Owi…
Differentially Private Federated Clustering over Non-IID Data
Yiwei Li, Shuai Wang, Chong-Yung Chi +1
In this paper, we investigate federated clustering (FedC) problem, that aims to accurately partition unlabeled data samples distributed over massive clients into finite clusters un…