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Privacy Preserving

Papers

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Showing 2001–2025 of 2975 papers

TitleStatusHype
Multi-Trigger-Key: Towards Multi-Task Privacy-Preserving In Deep Learning—0
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human—0
Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models—0
Navigating the Future of Federated Recommendation Systems with Foundation Models—0
Neighborhood and Global Perturbations Supported SAM in Federated Learning: From Local Tweaks To Global Awareness—0
Nemesis: Noise-randomized Encryption with Modular Efficiency and Secure Integration in Machine Learning Systems—0
Network Inversion for Training-Like Data Reconstruction—0
Neural Networks with (Low-Precision) Polynomial Approximations: New Insights and Techniques for Accuracy Improvement—0
Neural Tangent Kernel Empowered Federated Learning—0
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA—0
Neuromorphic Face Analysis: a Survey—0
NEUROSEC: FPGA-Based Neuromorphic Audio Security—0
A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models—0
No-audio speaking status detection in crowded settings via visual pose-based filtering and wearable acceleration—0
Node Injection Link Stealing Attack—0
Node-Level Differentially Private Graph Neural Networks—0
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy"—0
No Free Lunch Theorem for Privacy-Preserving LLM Inference—0
No Free Lunch Theorem for Security and Utility in Federated Learning—0
No Intruder, no Validity: Evaluation Criteria for Privacy-Preserving Text Anonymization—0
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling—0
Noiseless Privacy—0
Noise Resilient Over-The-Air Federated Learning In Heterogeneous Wireless Networks—0
Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape—0
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions—0
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