4 citations · 7 across the 5 of their papers we have counts for
5 papers
Pinching-antenna-enabled Federated Learning: Tail Latency, Participation, and Convergence Analysis
Yushen Lin, Zihan Chen, Zhiguo Ding
Federated learning (FL) in wireless networks is limited by straggler delays from unpredictable channel conditions. In this paper, we investigate the pinching-antenna system (PASS),…
Navigating Sparsities in High-Dimensional Linear Contextual Bandits
Rui Zhao, Zihan Chen, Zemin Zheng
High-dimensional linear contextual bandit problems remain a significant challenge due to the curse of dimensionality. Existing methods typically consider either the model parameter…
Voyager: An End-to-End Framework for Design-Space Exploration and Generation of DNN Accelerators
Kartik Prabhu, Jeffrey Yu, Xinyuan Allen Pan +5
While deep neural networks (DNNs) have achieved state-of-the-art performance in fields from computer vision to natural language processing, efficiently running these computationall…
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu +6
Federated Long-Tailed Learning (Fed-LT), a paradigm wherein data collected from decentralized local clients manifests a globally prevalent long-tailed distribution, has garnered co…
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer
Zikai Xiao, Zihan Chen, Songshang Liu +7
Data privacy and long-tailed distribution are the norms rather than the exception in many real-world tasks. This paper investigates a federated long-tailed learning (Fed-LT) task i…