2 citations · 2 across the 7 of their papers we have counts for
10 papers
Birdcast: Interest-aware BEV Multicasting for Infrastructure-assisted Collaborative Perception
Yanan Ma, Zhengru Fang, Yihang Tao +4
Vehicle-to-infrastructure collaborative perception (V2I-CP) leverages a high-vantage node to transmit supplementary information, i.e., bird's-eye-view (BEV) feature maps, to vehicl…
Multi-Server FL with Overlapping Clients: A Latency-Aware Relay Framework
Yun Ji, Zeyu Chen, Xiaoxiong Zhong +3
Multi-server Federated Learning (FL) has emerged as a promising solution to mitigate communication bottlenecks of single-server FL. In a typical multi-server FL architecture, the r…
UAV-enabled Computing Power Networks: Design and Performance Analysis under Energy Constraints
Yiqin Deng, Zhengru Fang, Senkang Hu +4
This paper presents an innovative framework that boosts computing power by utilizing ubiquitous computing power distribution and enabling higher computing node accessibility via ad…
UAV-enabled Computing Power Networks: Task Completion Probability Analysis
Yiqin Deng, Zhengru Fang, Senkang Hu +3
This paper presents an innovative framework that synergistically enhances computing performance through ubiquitous computing power distribution and dynamic computing node accessibi…
HFedMoE: Resource-aware Heterogeneous Federated Learning with Mixture-of-Experts
Zihan Fang, Zheng Lin, Senkang Hu +5
While federated learning (FL) enables fine-tuning of large language models (LLMs) without compromising data privacy, the substantial size of an LLM renders on-device training impra…
FedOC: Multi-Server FL with Overlapping Client Relays in Wireless Edge Networks
Yun Ji, Zeyu Chen, Xiaoxiong Zhong +3
Multi-server Federated Learning (FL) has emerged as a promising solution to mitigate communication bottlenecks of single-server FL. We focus on a typical multi-server FL architectu…