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Privacy Preserving

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Showing 2151–2175 of 2975 papers

TitleStatusHype
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization—0
IndicFed: A Federated Approach for Sentiment Analysis in Indic Languages—0
In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains—0
Gaussian Mechanisms Against Statistical Inference: Synthesis Tools—0
Privacy-Preserving Serverless Edge Learning with Decentralized Small Data—0
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series ClassificationCode0
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity ModelingCode0
Towards Understanding the Impact of Model Size on Differential Private Classification—0
Uncovering the Dark Side of Telegram: Fakes, Clones, Scams, and Conspiracy Movements—0
Node-Level Differentially Private Graph Neural Networks—0
Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability—0
Identifying Population Movements with Non-Negative Matrix Factorization from Wi-Fi User Counts in Smart and Connected Cities—0
FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps—0
Privacy-preserving Federated Learning for Residential Short Term Load Forecasting—0
Local Differential Privacy for Privacy-Preserving NLP Tasks—0
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated LearningCode0
Towards Privacy-Preserving Affect Recognition: A Two-Level Deep Learning Architecture—0
Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities—0
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning—0
Privacy-Preserving Distributed Average Consensus in Finite Time using Random Gossip—0
A methodology for training homomorphicencryption friendly neural networks—0
DVFL: A Vertical Federated Learning Method for Dynamic Data—0
Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits—0
Practical and Light-weight Secure Aggregation for Federated Submodel Learning—0
Reconstruction Attack on Instance Encoding for Language Understanding—0
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