Addressing Class Variable Imbalance in Federated Semi-supervised Learning

no code implementations • 21 Mar 2023 • Zehui Dong, Wenjing Liu, Siyuan Liu, Xingzhi Chen

Most of the current research is focusing on class imbalance with a fixed number of classes, while little attention is paid to data imbalance with a variable number of classes.

Enhanced Decentralized Federated Learning based on Consensus in Connected Vehicles

no code implementations • 22 Sep 2022 • Xiaoyan Liu, Zehui Dong, Zhiwei Xu, Siyuan Liu, Jie Tian

Federated learning (FL) is emerging as a new paradigm to train machine learning (ML) models in distributed systems, including vehicles in V2X networks.

Decision Making Federated Learning