Federated Unlearning
PulseAugur coverage of Federated Unlearning — every cluster mentioning Federated Unlearning across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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New benchmark 'Lethe' tests federated unlearning for medical imaging
Researchers have introduced Lethe, a new benchmark designed to evaluate federated unlearning methods specifically for medical imaging applications. Existing unlearning techniques, primarily tested on natural images, may…
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FedUP framework offers one-shot federated unlearning with reduced latency
Researchers have introduced FedUP, a novel one-shot federated unlearning framework designed to address the trade-off between data privacy and request latency. FedUP employs lightweight, pluggable filters that efficientl…
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New framework enables asynchronous federated unlearning for medical imaging models
Researchers have introduced Asynchronous Federated Unlearning with Invariance Calibration (AFU-IC), a new framework designed for medical imaging applications. This method addresses limitations in existing Federated Unle…