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Huabin Zhu

2 accepted papers

2024

Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data

CVPR 2024poster

Federated learning achieves effective performance in modeling decentralized data. In practice client data are not well-labeled which makes it potential for federated unsupervised learning (FUSL) with non-IID data. However the performance of existing FUSL methods suffers from insufficient representat…

Cited by 17SourcePDFScholar
2023

HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning

IJCAI 2023poster

Federated learning (FL) collaboratively models user data in a decentralized way. However, in the real world, non-identical and independent data distributions (non-IID) among clients hinder the performance of FL due to three issues, i.e., (1) the class statistics shifting, (2) the insufficient hierar…

Cited by 18SourcePDFScholar