arXiv Machine Learning July 10, 2026 By Ehsan Lari, Reza Arablouei, Stefan Werner

Communication-Efficient Byzantine-Robust Federated Conformal Prediction via Partial Model Sharing

Read the original on arXiv Machine Learning →

arXiv:2602. 18396v2 Announce Type: replace Abstract: We propose PRISM-FCP (Partial shaRing and robust calIbration with Statistical Margins for Federated Conformal Prediction), a communication-efficient Byzantine-robust federated conformal prediction framework that uses partial model sharing to mitigate stochastic model-poisoning attacks during training and histogram-based filtering to mitigate adversarial calibration submissions.

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