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Privacy Preserving

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Showing 1451–1475 of 2975 papers

TitleStatusHype
Federated Graph Learning with Adaptive Importance-based Sampling—0
Improving Correlation Capture in Generating Imbalanced Data using Differentially Private Conditional GANs—0
Improving Fairness and Robustness in End-to-End Speech Recognition through unsupervised clustering—0
Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty—0
Federated Graph Learning for Low Probability of Detection in Wireless Ad-Hoc Networks—0
Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning—0
Improving on-device speaker verification using federated learning with privacy—0
Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction—0
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning—0
In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains—0
Incentive Allocation in Vertical Federated Learning Based on Bankruptcy Problem—0
Federated Graph Condensation with Information Bottleneck Principles—0
Incentivizing Multi-Tenant Split Federated Learning for Foundation Models at the Network Edge—0
Differential Privacy May Have a Potential Optimization Effect on Some Swarm Intelligence Algorithms besides Privacy-preserving—0
A Distributed Differentially Private Algorithm for Resource Allocation in Unboundedly Large Settings—0
IndicFed: A Federated Approach for Sentiment Analysis in Indic Languages—0
Binary Federated Learning with Client-Level Differential Privacy—0
Industrial Scale Privacy Preserving Deep Neural Network—0
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation—0
Inference Attacks Against Face Recognition Model without Classification Layers—0
Federated Gradient Matching Pursuit—0
Federated Generative Privacy—0
Differential Privacy Under Class Imbalance: Methods and Empirical Insights—0
Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for Trustworthy AI—0
Correlated Differential Privacy: Feature Selection in Machine Learning—0
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