41 citations · 126 across the 35 of their papers we have counts for
6 papers · 1 filter
One-Bit Byzantine-Tolerant Distributed Learning via Over-the-Air Computation
Yuhan Yang, Youlong Wu, Yuning Jiang +1
Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous…
Features Disentangled Semantic Broadcast Communication Networks
Shuai Ma, Weining Qiao, Youlong Wu +6
Single-user semantic communications have attracted extensive research recently, but multi-user semantic broadcast communication (BC) is still in its infancy. In this paper, we prop…
Task-oriented Explainable Semantic Communications
Shuai Ma, Weining Qiao, Youlong Wu +6
Semantic communications utilize the transceiver computing resources to alleviate scarce transmission resources, such as bandwidth and energy. Although the conventional deep learnin…
Joint Beamforming and PD Orientation Design for Mobile Visible Light Communications
Shuai Ma, Jing Wang, Chun Du +5
In this paper, we propose joint beamforming and photo-detector (PD) orientation (BO) optimization schemes for mobile visible light communication (VLC) with the orientation adjustab…
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Yuhan Yang, Yong Zhou, Youlong Wu +1
Federated learning (FL), as a disruptive machine learning paradigm, enables the collaborative training of a global model over decentralized local datasets without sharing them. It…
Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
Shaoming Huang, Pengfei Zhang, Yijie Mao +2
Federated learning (FL) is recognized as a key enabling technology to support distributed artificial intelligence (AI) services in future 6G. By supporting decentralized data train…