Federated Learning over a Wireless Network: Distributed User Selection through Random Access

no code implementations • 7 Jul 2023 • Chen Sun, Shiyao Ma, Ce Zheng, Songtao Wu, Tao Cui, Lingjuan Lyu

This study proposes a network intrinsic approach of distributed user selection that leverages the radio resource competition mechanism in random access.

Fairness Federated Learning

Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis

no code implementations • 25 Sep 2022 • Jiawen Kang, Hongyang Du, Zonghang Li, Zehui Xiong, Shiyao Ma, Dusit Niyato, Yuan Li

Semantic communication, as a promising technology, has emerged to break through the Shannon limit, which is envisioned as the key enabler and fundamental paradigm for future 6G networks and applications, e. g., smart healthcare.

Image Retrieval Retrieval

Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones

no code implementations • 3 Jan 2022 • Zhe Zhang, Shiyao Ma, Zhaohui Yang, Zehui Xiong, Jiawen Kang, Yi Wu, Kejia Zhang, Dusit Niyato

This emerging technology relies on sharing ground truth labeled data between Unmanned Aerial Vehicle (UAV) swarms to train a high-quality automatic image recognition model.

Federated Learning Privacy Preserving

Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design

no code implementations • 26 Oct 2021 • Zhe Zhang, Shiyao Ma, Jiangtian Nie, Yi Wu, Qiang Yan, Xiaoke Xu, Dusit Niyato

In this paper, we present a robust semi-supervised FL system design, where the system aims to solve the problem of data availability and non-IID in FL.

Federated Learning