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Privacy Preserving

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Showing 2101–2150 of 2975 papers

TitleStatusHype
Masked LARk: Masked Learning, Aggregation and Reporting worKflowCode1
Locally Differentially Private Bayesian Inference—0
FedPrune: Towards Inclusive Federated Learning—0
DPCOVID: Privacy-Preserving Federated Covid-19 Detection—0
MarS-FL: Enabling Competitors to Collaborate in Federated Learning—0
Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization CollaborationsCode0
EDLaaS: Fully Homomorphic Encryption Over Neural Network Graphs for Vision and Private Strawberry Yield Forecasting—0
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy—0
Tackling the Local Bias in Federated Graph Learning—0
DistFL: Distribution-aware Federated Learning for Mobile ScenariosCode1
ML with HE: Privacy Preserving Machine Learning Inferences for Genome StudiesCode0
SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree—0
Privacy in Open Search: A Review of Challenges and Solutions—0
Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences—0
Distributed Reinforcement Learning for Privacy-Preserving Dynamic Edge Caching—0
FedParking: A Federated Learning based Parking Space Estimation with Parked Vehicle assisted Edge Computing—0
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes—0
A Federated Approach to Predict Emojis in Hindi Tweets—0
Sparse Distillation: Speeding Up Text Classification by Using Bigger Student ModelsCode1
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling—0
Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing—0
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture—0
Efficient privacy-preserving inference for convolutional neural networks—0
Occupancy Estimation from Thermal Images—0
FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning—0
Infinitely Divisible Noise in the Low Privacy RegimeCode0
Sharing FANCI Features: A Privacy Analysis of Feature Extraction for DGA Detection—0
Not all noise is accounted equally: How differentially private learning benefits from large sampling ratesCode0
Federated Phish Bowl: LSTM-Based Decentralized Phishing Email Detection—0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Aura: Privacy-preserving Augmentation to Improve Test Set Diversity in Speech EnhancementCode0
GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learning—0
MilliTRACE-IR: Contact Tracing and Temperature Screening via mm-Wave and Infrared Sensing—0
Complex-valued Federated Learning with Differential Privacy and MRI Applications—0
Neural Tangent Kernel Empowered Federated Learning—0
Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning—0
Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling under Data Governance—0
Secure Byzantine-Robust Distributed Learning via Clustering—0
Communication-Efficient Federated Learning with Binary Neural NetworksCode1
FedDQ: Communication-Efficient Federated Learning with Descending Quantization—0
Distributed Privacy-Preserving Electric Vehicle Charging Control Based on Secret Sharing—0
Dirichlet Mechanism for Differentially Private KL Divergence MinimizationCode0
One-Bit Matrix Completion with Differential Privacy—0
A Privacy-preserving Distributed Training Framework for Cooperative Multi-agent Deep Reinforcement Learning—0
Federated Contrastive Learning for Privacy-Preserving Unpaired Image-to-Image Translation—0
Larger Model Causes Lower Classification Accuracy Under Differential Privacy: Reason and Solution—0
Privacy-preserving Task-Agnostic Vision Transformer for Image ProcessingCode0
Practical and Private Heterogeneous Federated Learning—0
Demystifying Hyperparameter Optimization in Federated Learning—0
Multi-Trigger-Key: Towards Multi-Task Privacy-Preserving In Deep Learning—0
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