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Privacy Preserving

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Showing 2026–2050 of 2975 papers

TitleStatusHype
Stratified cross-validation for unbiased and privacy-preserving federated learning—0
Striking a Balance: An Optimal Mechanism Design for Heterogenous Differentially Private Data Acquisition for Logistic Regression—0
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors—0
Study of the performance and scalability of federated learning for medical imaging with intermittent clients—0
Sub-Linear Privacy-Preserving Near-Neighbor Search—0
Submodular Combinatorial Information Measures with Applications in Machine Learning—0
Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning—0
Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images—0
Successive Point-of-Interest Recommendation with Local Differential Privacy—0
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-Device Inference—0
Suppressing Noise from Built Environment Datasets to Reduce Communication Rounds for Convergence of Federated Learning—0
Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications—0
Survey of Privacy-Preserving Collaborative Filtering—0
S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning—0
SwiftAgg+: Achieving Asymptotically Optimal Communication Loads in Secure Aggregation for Federated Learning—0
SwiftAgg: Communication-Efficient and Dropout-Resistant Secure Aggregation for Federated Learning with Worst-Case Security Guarantees—0
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning—0
Swing Distillation: A Privacy-Preserving Knowledge Distillation Framework—0
Switch-Based Multi-Part Neural Network—0
SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers—0
Synergising Hierarchical Data Centers and Power Networks: A Privacy-Preserving Approach—0
SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining—0
Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications—0
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs—0
Synthetic Data and Simulators for Recommendation Systems: Current State and Future Directions—0
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