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20212025
most citedCommunication-Efficient Federated Learning with Binary Neural Networks

51 citations · 51 across the 3 of their papers we have counts for

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5 papers

eess.SP2025

Diffusion Models for Wireless Transceivers: From Pilot-Efficient Channel Estimation to AI-Native 6G Receivers

Yuzhi Yang, Sen Yan, Weijie Zhou +4

With the development of artificial intelligence (AI) techniques, implementing AI-based techniques to improve wireless transceivers becomes an emerging research topic. Within this c…

eess.SP2025

Integrated Sensing, Communication, and Positioning in Cellular Vehicular Networks

Xin Tong, Zhaoyang Zhang, Yuzhi Yang +4

In this correspondence, a novel integrated sensing and communication (ISAC) framework is proposed to accomplish data communication, vehicle positioning, and environment sensing sim…

eess.SP2025

Generative Diffusion Receivers: Achieving Pilot-Efficient MIMO-OFDM Communications

Yuzhi Yang, Omar Alhussein, Atefeh Arani +2

This paper focuses on wireless multiple-input multiple-output (MIMO)-orthogonal frequency division multiplex (OFDM) receivers. Traditional wireless receivers have relied on mathema…

eess.SP2022

Over-the-Air Split Learning with MIMO-Based Neural Network and Constellation-Based Activation

Yuzhi Yang, Zhaoyang Zhang, Zhaohui Yang

This paper investigates a communication-efficient split learning (SL) over multiple-input multiple-output (MIMO) communication system. In particular, we mathematically decompose th…

cs.LG202151 cited

Communication-Efficient Federated Learning with Binary Neural Networks

Yuzhi Yang, Zhaoyang Zhang, Qianqian Yang

Federated learning (FL) is a privacy-preserving machine learning setting that enables many devices to jointly train a shared global model without the need to reveal their data to a…