Mechanisms for Robust Local Differential Privacy. [PDF]
Entropy (Basel)Lopuhaä-Zwakenberg M, Goseling J.
europepmc +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
An empirical assessment of differential privacy in real-world observational data: a case-control study of asthma exacerbation in UK Biobank linked with electronic health records. [PDF]
J Am Med Inform AssocMizani MA, Sheikh A, Banerjee A.
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Federated learning and differential privacy: Machine learning and deep learning for biomedical image data classification. [PDF]
Digit HealthWassan S +4 more
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Federated learning with differential privacy via fast Fourier transform for tighter-efficient combining. [PDF]
Sci RepGuo S, Yang J, Long S, Wang X, Liu G.
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Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy-Added Federated Learning Settings: Quantitative Study. [PDF]
JMIR Ment HealthBenouis M, Andre E, Can YS.
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Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy. [PDF]
Proceedings VLDB EndowmentKato F +4 more
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Differential Privacy and Security [PDF]
Fundamenta Informaticae, 2016 A quantification of process’s security by differential privacy is defined and studied in the framework of probabilistic process algebras. The resulting (quantitative) security properties are investigated and compared with other (qualitative and quantitative) security notions.
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