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Privacy Preserving

Papers

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Showing 2001–2050 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
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices—0
No Peeking through My Windows: Conserving Privacy in Personal Drones—0
No-Regret Algorithms for Private Gaussian Process Bandit Optimization—0
Norm-Bounded Low-Rank Adaptation—0
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud—0
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning—0
Novelty Messages Filtering for Multi Agent Privacy-preserving Planning—0
Oblivion: Mitigating Privacy Leaks by Controlling the Discoverability of Online Information—0
Oblivious Sampling Algorithms for Private Data Analysis—0
Obscure: Information-Theoretically Secure, Oblivious, and Verifiable Aggregation Queries on Secret-Shared Outsourced Data -- Full Version—0
Occupancy Estimation from Thermal Images—0
OcularAge: A Comparative Study of Iris and Periocular Images for Pediatric Age Estimation—0
On Achieving Privacy-Preserving State-of-the-Art Edge Intelligence—0
On Aggregation Performance in Privacy Conscious Hierarchical Flexibility Coordination Schemes—0
On a Utilitarian Approach to Privacy Preserving Text Generation—0
Onboard Optimization and Learning: A Survey—0
On-device Training: A First Overview on Existing Systems—0
One-Bit Matrix Completion with Differential Privacy—0
One-Shot Federated Unsupervised Domain Adaptation with Scaled Entropy Attention and Multi-Source Smoothed Pseudo Labeling—0
On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning—0
On Immutable Memory Systems for Artificial Agents: A Blockchain-Indexed Automata-Theoretic Framework Using ECDH-Keyed Merkle Chains—0
On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects—0
Online Human Activity Recognition Employing Hierarchical Hidden Markov Models—0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models—0
On Polynomial Approximations for Privacy-Preserving and Verifiable ReLU Networks—0
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