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Privacy Preserving

Papers

Showing 676700 of 2975 papers

TitleStatusHype
Privacy-Preserving Distributed Defense Framework for DC Microgrids Against Exponentially Unbounded False Data Injection Attacks0
Generalizing in Net-Zero Microgrids: A Study with Federated PPO and TRPOCode0
Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection0
Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing0
Towards nation-wide analytical healthcare infrastructures: A privacy-preserving augmented knee rehabilitation case studyCode0
SafeSynthDP: Leveraging Large Language Models for Privacy-Preserving Synthetic Data Generation Using Differential Privacy0
Reconciling Privacy and Explainability in High-Stakes: A Systematic InquiryCode0
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis0
Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints0
FFA Sora, video generation as fundus fluorescein angiography simulator0
Better Knowledge Enhancement for Privacy-Preserving Cross-Project Defect Prediction0
Asynchronous Federated Learning: A Scalable Approach for Decentralized Machine LearningCode0
Dataset for Real-World Human Action Detection Using FMCW mmWave Radar0
Modular Conversational Agents for Surveys and Interviews0
Label Privacy in Split Learning for Large Models with Parameter-Efficient TrainingCode0
CBNN: 3-Party Secure Framework for Customized Binary Neural Networks Inference0
Privacy in Fine-tuning Large Language Models: Attacks, Defenses, and Future Directions0
Benchmarking LLMs and SLMs for patient reported outcomes0
FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks0
Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation0
Clio: Privacy-Preserving Insights into Real-World AI Use0
Federated Learning and RAG Integration: A Scalable Approach for Medical Large Language Models0
FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning0
Towards privacy-preserving cooperative control via encrypted distributed optimization0
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