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Catuscia Palamidessi

Mitigating Membership Inference Vulnerability in Personalized Federated Learning

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Mar 12, 2025
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Jeffrey's update rule as a minimizer of Kullback-Leibler divergence

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Feb 21, 2025
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Comparing privacy notions for protection against reconstruction attacks in machine learning

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Feb 06, 2025
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Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks

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Feb 03, 2025
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Bayes' capacity as a measure for reconstruction attacks in federated learning

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Jun 19, 2024
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A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results

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May 23, 2024
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On the Impact of Multi-dimensional Local Differential Privacy on Fairness

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Dec 08, 2023
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Causal Discovery Under Local Privacy

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Nov 15, 2023
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Online Sensitivity Optimization in Differentially Private Learning

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Oct 02, 2023
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Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond

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Sep 01, 2023
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