SOTAVerified

Privacy Preserving

Papers

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Showing 1401–1450 of 2975 papers

TitleStatusHype
Differentially Private Multi-Agent Planning for Logistic-like Problems—0
High-Precision Bootstrapping for Approximate Homomorphic Encryption by Error Variance Minimization—0
High-Resolution WiFi Imaging with Reconfigurable Intelligent Surfaces—0
Histopathological Image Classification and Vulnerability Analysis using Federated Learning—0
HLF-FSL. A Decentralized Federated Split Learning Solution for IoT on Hyperledger Fabric—0
HOG feature extraction from encrypted images for privacy-preserving machine learning—0
cpSGD: Communication-efficient and differentially-private distributed SGD—0
A Survey of Graph Unlearning—0
Encrypted Linear Contextual Bandit—0
Homomorphic Encryption and Federated Learning based Privacy-Preserving CNN Training: COVID-19 Detection Use-Case—0
Homomorphic WiSARDs: Efficient Weightless Neural Network training over encrypted data—0
Hot PATE: Private Aggregation of Distributions for Diverse Task—0
How Does Knowledge of the AUC Constrain the Set of Possible Ground-truth Labelings?—0
How low can you go? Privacy-preserving people detection with an omni-directional camera—0
Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients—0
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?—0
Federated Knowledge Recycling: Privacy-Preserving Synthetic Data Sharing—0
Concentrated Differentially Private and Utility Preserving Federated Learning—0
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning—0
Beyond Identity: What Information Is Stored in Biometric Face Templates?—0
How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink Channels—0
How Secure are Deep Learning Algorithms from Side-Channel based Reverse Engineering?—0
How to Collaborate: Towards Maximizing the Generalization Performance in Cross-Silo Federated Learning—0
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning—0
How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing—0
Differentially Private Recursive Least Squares Estimation for ARX Systems with Multi-Participants—0
Federated Instruction Tuning of LLMs with Domain Coverage Augmentation—0
HW-SW Optimization of DNNs for Privacy-preserving People Counting on Low-resolution Infrared Arrays—0
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning—0
Distributed Machine Learning in D2D-Enabled Heterogeneous Networks: Architectures, Performance, and Open Challenges—0
AI-VERDE: A Gateway for Egalitarian Access to Large Language Model-Based Resources For Educational Institutions—0
IndicFed: A Federated Approach for Sentiment Analysis in Indic Languages—0
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing—0
Hyperdimensional Computing as a Rescue for Efficient Privacy-Preserving Machine Learning-as-a-Service—0
Hyper-parameter Optimization for Federated Learning with Step-wise Adaptive Mechanism—0
I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption—0
ID^3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition—0
Federated In-Context LLM Agent Learning—0
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation—0
Addressing the cold start problem in privacy preserving content-based recommender systems using hypercube graphs—0
Federated Graph Learning with Adaptive Importance-based Sampling—0
I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies—0
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale—0
Image-Hashing-Based Anomaly Detection for Privacy-Preserving Online Proctoring—0
Image Transformation Network for Privacy-Preserving Deep Neural Networks and Its Security Evaluation—0
Immersion and Invariance-based Coding for Privacy-Preserving Federated Learning—0
Federated Graph Learning for Low Probability of Detection in Wireless Ad-Hoc Networks—0
Improved Algorithms for Differentially Private Language Model Alignment—0
Improved Privacy-Preserving PCA Using Optimized Homomorphic Matrix Multiplication—0
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning—0
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