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Privacy Preserving

Papers

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Showing 251–300 of 2975 papers

TitleStatusHype
CryptoNN: Training Neural Networks over Encrypted DataCode1
Continual atlas-based segmentation of prostate MRICode1
Fair Federated Learning under Domain Skew with Local Consistency and Domain DiversityCode1
Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated DistillationCode1
CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi SensingCode1
DeceFL: A Principled Decentralized Federated Learning FrameworkCode1
Communication-Efficient Federated Learning with Binary Neural NetworksCode1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer LearningCode1
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionCode1
CipherPrune: Efficient and Scalable Private Transformer InferenceCode1
Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New BaselineCode1
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?Code1
Attack-Aware Noise Calibration for Differential PrivacyCode1
Position: Considerations for Differentially Private Learning with Large-Scale Public PretrainingCode1
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID DataCode1
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPUCode1
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity TheoryCode1
A Survey for Federated Learning Evaluations: Goals and MeasuresCode1
Exploring Federated Unlearning: Review, Comparison, and InsightsCode1
Data Valuation and Detections in Federated LearningCode1
CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning ApproachesCode1
BrainGuard: Privacy-Preserving Multisubject Image Reconstructions from Brain ActivitiesCode1
Differentially Private Federated Learning: A Client Level PerspectiveCode1
DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data GenerationCode1
Can Foundation Models Help Us Achieve Perfect Secrecy?Code1
DistFL: Distribution-aware Federated Learning for Mobile ScenariosCode1
Domain-Invariant Representation Learning from EEG with Private EncodersCode1
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt EngineerCode1
Concentrated Differential Privacy: Simplifications, Extensions, and Lower BoundsCode1
Defending against Backdoors in Federated Learning with Robust Learning RateCode1
EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud ComputingCode1
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platformCode1
MMASD+: A Novel Dataset for Privacy-Preserving Behavior Analysis of Children with Autism Spectrum DisorderCode1
A Secure and Efficient Distributed Semantic Communication System for Heterogeneous Internet of Things—0
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning—0
AI and Democracy's Digital Identity Crisis—0
A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks—0
Artificial Intelligence for Secured Information Systems in Smart Cities: Collaborative IoT Computing with Deep Reinforcement Learning and Blockchain—0
A Hybrid Federated Kernel Regularized Least Squares Algorithm—0
Additively Homomorphical Encryption based Deep Neural Network for Asymmetrically Collaborative Machine Learning—0
Artificial Intelligence at the Edge—0
Artemis: HE-Aware Training for Efficient Privacy-Preserving Machine Learning—0
Large-Scale Secure XGB for Vertical Federated Learning—0
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection—0
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning—0
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling—0
Bayesian Federated Learning: A Survey—0
Bayesian Federated Learning over Wireless Networks—0
A Review on Machine Unlearning—0
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack—0
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