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Privacy Preserving

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Showing 2051–2100 of 2975 papers

TitleStatusHype
Privacy-Preserving Speech Representation Learning using Vector Quantization—0
Communication-Efficient Federated Distillation with Active Data Sampling—0
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation—0
No Free Lunch Theorem for Security and Utility in Federated Learning—0
FedSyn: Synthetic Data Generation using Federated Learning—0
Federated Remote Physiological Measurement with Imperfect Data—0
Similarity-based Label Inference Attack against Training and Inference of Split Learning—0
Conditional Synthetic Data Generation for Personal Thermal Comfort Models—0
Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributesCode0
Towards Efficient and Stable K-Asynchronous Federated Learning with Unbounded Stale Gradients on Non-IID Data—0
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data—0
FedREP: Towards Horizontal Federated Load Forecasting for Retail Energy Providers—0
Estimating Model Performance on External Samples from Their Limited Statistical CharacteristicsCode0
Privacy-preserving machine learning with tensor networksCode0
How reparametrization trick broke differentially-private text representation learningCode0
Differential privacy for symmetric log-concave mechanismsCode0
FlowSense: Monitoring Airflow in Building Ventilation Systems Using Audio SensingCode0
Privacy-Preserving In-Bed Pose Monitoring: A Fusion and Reconstruction Study—0
Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol DatasetCode0
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy—0
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices—0
SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service—0
Fair Division with Money and Prices—0
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey—0
Privacy Preserving Visual Question Answering—0
Do Gradient Inversion Attacks Make Federated Learning Unsafe?—0
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data ReleaseCode0
Privacy-preserving Generative Framework Against Membership Inference Attacks—0
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation—0
Backpropagation Clipping for Deep Learning with Differential PrivacyCode0
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection—0
FedQAS: Privacy-aware machine reading comprehension with federated learningCode0
PrivFair: a Library for Privacy-Preserving Fairness AuditingCode0
SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees—0
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks—0
Locally Differentially Private Distributed Deep Learning via Knowledge DistillationCode0
Lossy Compression of Noisy Data for Private and Data-Efficient Learning—0
CECILIA: Comprehensive Secure Machine Learning FrameworkCode0
ABG: A Multi-Party Mixed Protocol Framework for Privacy-Preserving Cooperative Learning—0
Energy-Aware Edge Association for Cluster-based Personalized Federated Learning—0
Linear Model Against Malicious Adversaries with Local Differential Privacy—0
Training Differentially Private Models with Secure Multiparty Computation—0
PrivPAS: A real time Privacy-Preserving AI System and applied ethics—0
Efficient Privacy Preserving Logistic Regression for Horizontally Distributed Data—0
Comparative assessment of federated and centralized machine learning—0
Privacy-Aware Crowd Labelling for Machine Learning Tasks—0
Improved Regret for Differentially Private Exploration in Linear MDP—0
A Privacy-Preserving Image Retrieval Scheme with a Mixture of Plain and EtC Images—0
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs—0
Lessons from the AdKDD'21 Privacy-Preserving ML Challenge—0
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