Web: http://arxiv.org/abs/2206.03655

June 20, 2022, 1:11 a.m. | Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding

cs.LG updates on arXiv.org arxiv.org

Personalized Federated Learning (pFL), which utilizes and deploys distinct
local models, has gained increasing attention in recent years due to its
success in handling the statistical heterogeneity of FL clients. However,
standardized evaluation and systematical analysis of diverse pFL methods remain
a challenge. Firstly, the highly varied datasets, FL simulation settings and
pFL implementations prevent fast and fair comparisons of pFL methods. Secondly,
the effectiveness and robustness of pFL methods are under-explored in various
practical scenarios, such as new clients …

arxiv benchmark federated learning learning lg personalized

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