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News/Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata
arxiv
PublishedJuly 31, 2026 at 4:00 AM
▲bullish

Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata

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Publisher summary· verbatim

arXiv:2607.28338v1 Announce Type: new Abstract: Clustered Federated Learning (CFL) addresses data heterogeneity in federated settings by grouping clients with similar data distributions to enable effective training. Existing methods face a trade-off between privacy preservation, communication cost,

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