SOTAVerified

Privacy Preserving

Papers

Showing 551575 of 2975 papers

TitleStatusHype
Exploring the Landscape for Generative Sequence Models for Specialized Data SynthesisCode0
FADAS: Towards Federated Adaptive Asynchronous OptimizationCode0
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial LearningCode0
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series ClassificationCode0
Estimating Model Performance on External Samples from Their Limited Statistical CharacteristicsCode0
Experimenting with Normalization Layers in Federated Learning on non-IID scenariosCode0
Enhancing Small Medical Learners with Privacy-preserving Contextual PromptingCode0
Enhanced Outsourced and Secure Inference for Tall Sparse Decision TreesCode0
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST)Code0
Exploring Federated Pruning for Large Language ModelsCode0
Data Augmentation Techniques for Cross-Domain WiFi CSI-based Human Activity RecognitionCode0
Empathy Detection from Text, Audiovisual, Audio or Physiological Signals: A Systematic Review of Task Formulations and Machine Learning MethodsCode0
A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep LearningCode0
DartBlur: Privacy Preservation With Detection Artifact SuppressionCode0
Empowering Data Mesh with Federated LearningCode0
Efficient and Privacy-Preserved Link Prediction via Condensed GraphsCode0
A Lightweight and Secure Deep Learning Model for Privacy-Preserving Federated Learning in Intelligent EnterprisesCode0
DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networksCode0
DRL-Based Resource Allocation for Motion Blur Resistant Federated Self-Supervised Learning in IoVCode0
DPM: Clustering Sensitive Data through SeparationCode0
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement LearningCode0
ER-AE: Differentially Private Text Generation for Authorship AnonymizationCode0
DP-NMT: Scalable Differentially-Private Machine TranslationCode0
DP-RTFL: Differentially Private Resilient Temporal Federated Learning for Trustworthy AI in Regulated IndustriesCode0
Domain Borders Are There to Be Crossed With Federated Few-Shot AdaptationCode0
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