Concept

Data re-identification

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Data re-identification

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Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Differentially private multi-agent constraint optimization

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Differentially Private Multi-Agent Constraint Optimization

Utility/privacy trade-off as regularized optimal transport

TEE-based decentralized recommender systems: The raw data sharing redemption

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

Private and Secure Distributed Learning

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Differentially private multi-agent constraint optimization

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Differentially Private Multi-Agent Constraint Optimization

Utility/privacy trade-off as regularized optimal transport

TEE-based decentralized recommender systems: The raw data sharing redemption

Private and Secure Distributed Learning

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building