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Privacy Preserving

Papers

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Showing 1001–1050 of 2975 papers

TitleStatusHype
Efficient Data Distribution Estimation for Accelerated Federated Learning—0
Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agent—0
FedCL: Federated Contrastive Learning for Privacy-Preserving Recommendation—0
Efficient Cross-Domain Federated Learning by MixStyle Approximation—0
FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning—0
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants—0
Efficient Classification of SARS-CoV-2 Spike Sequences Using Federated Learning—0
FedCPC: An Effective Federated Contrastive Learning Method for Privacy Preserving Early-Stage Alzheimer's Speech Detection—0
A privacy-preserving, distributed and cooperative FCM-based learning approach for cancer research—0
FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning—0
Efficient and Private: Memorisation under differentially private parameter-efficient fine-tuning in language models—0
Efficient and Privacy Preserving Group Signature for Federated Learning—0
FedDCT: A Dynamic Cross-Tier Federated Learning Framework in Wireless Networks—0
Efficient and Personalized Mobile Health Event Prediction via Small Language Models—0
FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation—0
FedDiSC: A Computation-efficient Federated Learning Framework for Power Systems Disturbance and Cyber Attack Discrimination—0
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation—0
FedDMF: Privacy-Preserving User Attribute Prediction using Deep Matrix Factorization—0
FedDP: Privacy-preserving method based on federated learning for histopathology image segmentation—0
FedDQ: Communication-Efficient Federated Learning with Descending Quantization—0
Cali3F: Calibrated Fast Fair Federated Recommendation System—0
FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels—0
A privacy-preserving distributed computational approach for distributed locational marginal prices—0
Active Inference for Energy Control and Planning in Smart Buildings and Communities—0
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data—0
HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection—0
Efficient Adaptive Federated Optimization of Federated Learning for IoT—0
Effect of Homomorphic Encryption on the Performance of Training Federated Learning Generative Adversarial Networks—0
CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning—0
Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning—0
Effectively Heterogeneous Federated Learning: A Pairing and Split Learning Based Approach—0
C^3DRec: Cloud-Client Cooperative Deep Learning for Temporal Recommendation in the Post-GDPR Era—0
A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors—0
Effective and Privacy preserving Tabular Data Synthesizing—0
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective—0
Byzantine-Robust and Privacy-Preserving Framework for FedML—0
eFedDNN: Ensemble based Federated Deep Neural Networks for Trajectory Mode Inference—0
EDLaaS: Fully Homomorphic Encryption Over Neural Network Graphs for Vision and Private Strawberry Yield Forecasting—0
Byzantine-Resilient Secure Federated Learning—0
A Privacy Preserving Data Publishing Middleware for Unstructured, Textual Social Media Data—0
A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction—0
EdgePrompt: A Distributed Key-Value Inference Framework for LLMs in 6G Networks—0
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises—0
Edge Private Graph Neural Networks with Singular Value Perturbation—0
Bytes Are All You Need: Transformers Operating Directly On File Bytes—0
A Privacy-Preserving Content-Based Image Retrieval Scheme Allowing Mixed Use Of Encrypted And Plain Images—0
Edge-assisted U-Shaped Split Federated Learning with Privacy-preserving for Internet of Things—0
(ε, δ)-Differentially Private Partial Least Squares Regression—0
BUNET: Blind Medical Image Segmentation Based on Secure UNET—0
EchoFlow: A Foundation Model for Cardiac Ultrasound Image and Video Generation—0
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