BriefGPT.xyz
Oct, 2022
探索和缓解异构联邦学习中的维度崩溃
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
HTML
PDF
Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Y. F. Tan, Song Bai
TL;DR
提出了一种名为 FedDecorr 的新方法,可以在联邦学习中有效缓解数据异构性造成的维度崩溃问题。该方法鼓励表示的不同维度不相关,并且在标准基准数据集上比基线方法表现更好。
Abstract
federated learning
aims to train models collaboratively across different clients without the sharing of data for privacy considerations. However, one major challenge for this learning paradigm is the {\em
data heterogen
→