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20102026
most citedWhy Should I Choose You? AutoXAI: A Framework for Selecting and Tuning eXplainable AI Solutions

17 citations · 51 across the 9 of their papers we have counts for

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cs.LG2026

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

Michael Ben Ali, Imen Megdiche, André Péninou +1

Clustered Federated Learning (CFL) addresses data heterogeneity in federated settings by grouping clients with similar data distributions to enable effective training. Existing met…