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Baocheng Geng

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#machine learning Preprint Aug 2026

CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning

This work proposes Class-wise Reliability-Aware Distillation (CRAD), which, per class, first discards teachers that disagree with the peer consensus and then takes a weighted average of the rest, weighting each teacher by its per-class reliability (precision, or inverse variance).

Baraa Bilbeisi, Meng-Chen Fan, Bao-Cheng Geng et al. · 1 citation