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Author

Tobias Schlagenhauf

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Book Open access Aug 2026

SensCluster: Sensitivity-Guided Client Clustering for Feature-Skewed Federated Learning

SensCluster is proposed, a novel sensitivity-aware CFL framework that constructs compact client representations by selecting parameters that are most responsive to local feature distributions, and consistently outperforms state-of-the-art CFL methods across diverse feature skew scenarios.

Jiaqi Wang, Tobias Schlagenhauf, Setareh Maghsudi · 0 citations
Book Open access Aug 2026

SensCluster: Sensitivity-Guided Client Clustering for Feature-Skewed Federated Learning

Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, but its performance degrades significantly under heterogeneous data distributions. While Clustered Federated Learning (CFL) mitigates heterogeneity by grouping similar clients, most existing methods primari...

Jiaqi Wang, Tobias Schlagenhauf, Setareh Maghsudi · 0 citations

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