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May, 2024
基于双向筛选的联邦学习在部分类别不相交数据上的应用
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
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Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang...
TL;DR
FedGELA 是一种新方法,通过将分类器全局固定为一种Simplex ETF,并针对个人分布进行本地适应,从而在联合学习的整体视图和局部视图中实现公平而平等的鉴别,解决了部分类不相交数据(PCDD)带来的挑战
Abstract
partially class-disjoint data
(PCDD), a common yet under-explored data formation where each client contributes a part of classes (instead of all classes) of samples, severely challenges the performance of
federated algo
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