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Privacy Preserving

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Showing 1901–1925 of 2975 papers

TitleStatusHype
Local Differential Privacy for Privacy-Preserving NLP Tasks—0
Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models—0
Locally Differentially Private Bayesian Inference—0
(Locally) Differentially Private Combinatorial Semi-Bandits—0
Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems—0
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes—0
Locally Private Sampling with Public Data—0
Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data—0
LoMar: A Local Defense Against Poisoning Attack on Federated Learning—0
LongEval-Retrieval: French-English Dynamic Test Collection for Continuous Web Search Evaluation—0
Long-Term Conversation Analysis: Privacy-Utility Trade-off under Noise and Reverberation—0
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement—0
Loss-Guided Model Sharing and Local Learning Correction in Decentralized Federated Learning for Crop Disease Classification—0
Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation—0
Lossless Privacy-Preserving Aggregation for Decentralized Federated Learning—0
Low-Cost Privacy-Preserving Decentralized Learning—0
Low-Latency Privacy-Preserving Deep Learning Design via Secure MPC—0
Privacy Preserving Location Data Publishing: A Machine Learning Approach—0
Machine Learning Algorithms for Active Monitoring of High Performance Computing as a Service (HPCaaS) Cloud Environments—0
Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities—0
MAGNETO: Fingerprinting USB Flash Drives via Unintentional Magnetic Emissions—0
Majority Vote for Distributed Differentially Private Sign Selection—0
Protecting Split Learning by Potential Energy Loss—0
Making the Shoe Fit: Architectures, Initializations, and Tuning for Learning with Privacy—0
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures—0
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