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May, 2023
部分个性化联邦学习：打破数据异构的诅咒
Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity
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Konstantin Mishchenko, Rustem Islamov, Eduard Gorbunov, Samuel Horváth
TL;DR
本文介绍了一种部分个性化的联邦学习（FL）方法，旨在在个性化和全局训练的灵活性之间取得平衡，并提出了一种简单的算法来解决数据异构性问题。
Abstract
We present a partially personalized formulation of
federated learning
(FL) that strikes a balance between the flexibility of
personalization
and cooperativeness of
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