SOTAVerified

Privacy Preserving

Papers

Showing 251300 of 2975 papers

TitleStatusHype
FedSim: Similarity guided model aggregation for Federated LearningCode1
FedTP: Federated Learning by Transformer PersonalizationCode1
Federated Learning with Spiking Neural NetworksCode1
Federated Few-Shot Learning for Mobile NLPCode1
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity LearningCode1
Fed-MUnet: Multi-modal Federated Unet for Brain Tumor SegmentationCode1
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated LearningCode1
FedMatch: Federated Learning Over Heterogeneous Question Answering DataCode1
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platformCode1
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise HeterogeneityCode1
FedFly: Towards Migration in Edge-based Distributed Federated LearningCode1
Attacks on Image Encryption Schemes for Privacy-Preserving Deep Neural NetworksCode1
BrainGuard: Privacy-Preserving Multisubject Image Reconstructions from Brain ActivitiesCode1
Defending against Backdoors in Federated Learning with Robust Learning RateCode1
FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack DetectionCode1
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated LearningCode1
FedVLN: Privacy-preserving Federated Vision-and-Language NavigationCode1
A Survey for Federated Learning Evaluations: Goals and MeasuresCode1
Attack-Aware Noise Calibration for Differential PrivacyCode1
Federated Transfer Learning for EEG Signal ClassificationCode1
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal DecouplingCode1
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?Code1
Can Foundation Models Help Us Achieve Perfect Secrecy?Code1
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity TheoryCode1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
Generative Autoregressive Transformers for Model-Agnostic Federated MRI ReconstructionCode1
CipherPrune: Efficient and Scalable Private Transformer InferenceCode1
Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision SensorsCode1
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsificationCode1
Communication-Efficient Federated Learning with Binary Neural NetworksCode1
Heterogeneous Graph Neural Network for Privacy-Preserving RecommendationCode1
How Privacy-Preserving are Line Clouds? Recovering Scene Details from 3D LinesCode1
Production of Categorical Data Verifying Differential Privacy: Conception and Applications to Machine LearningCode1
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
Federated Learning with Reduced Information Leakage and ComputationCode0
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and ProtectionCode0
Federated Learning for Time-Series Healthcare Sensing with Incomplete ModalitiesCode0
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile AnalyticsCode0
ARIA: On the Interaction Between Architectures, Initialization and Aggregation Methods for Federated Visual ClassificationCode0
A Hybrid Approach to Privacy-Preserving Federated LearningCode0
Federated Learning for Privacy-Preserving Feedforward Control in Multi-Agent SystemsCode0
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data SourcesCode0
Federated Causal Inference from Observational DataCode0
Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical ApproachesCode0
Federated Frank-Wolfe AlgorithmCode0
1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential PrivacyCode0
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity ModelingCode0
FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain RecommendationCode0
Position: On-Premises LLM Deployment Demands a Middle Path: Preserving Privacy Without Sacrificing Model ConfidentialityCode0
Arbitrary Decisions are a Hidden Cost of Differentially Private TrainingCode0
Show:102550
← PrevPage 6 of 60Next →

No leaderboard results yet.