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Privacy Preserving

Papers

Showing 26262650 of 2975 papers

TitleStatusHype
Differentially Private Knowledge Distillation via Synthetic Text GenerationCode0
Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol DatasetCode0
FastLloyd: Federated, Accurate, Secure, and Tunable k-Means Clustering with Differential PrivacyCode0
FedSKC: Federated Learning with Non-IID Data via Structural Knowledge CollaborationCode0
BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion AttacksCode0
FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural NetworksCode0
Speech privacy-preserving methods using secret key for convolutional neural network models and their robustness evaluationCode0
A Speech Representation Anonymization Framework via Selective Noise PerturbationCode0
Adversarial Privacy-preserving FilterCode0
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial LearningCode0
Variational Bayes In Private Settings (VIPS)Code0
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative ModelsCode0
A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from SpeechCode0
PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation LearningCode0
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome PredictionCode0
Privacy Preserving Image RegistrationCode0
Fair Federated Data Clustering through Personalization: Bridging the Gap between Diverse Data DistributionsCode0
Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional GroupsCode0
Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the operating roomCode0
A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep LearningCode0
FADAS: Towards Federated Adaptive Asynchronous OptimizationCode0
CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat DetectionCode0
Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution EnvironmentsCode0
Privacy and Trust Redefined in Federated Machine LearningCode0
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate PerturbationsCode0
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