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Privacy Preserving

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Showing 1651–1700 of 2975 papers

TitleStatusHype
FedQP: Towards Accurate Federated Learning using Quadratic Programming Guided Mutation—0
FedRBE -- a decentralized privacy-preserving federated batch effect correction tool for omics data based on limma—0
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning—0
FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning—0
FedREP: Towards Horizontal Federated Load Forecasting for Retail Energy Providers—0
FedSampling: A Better Sampling Strategy for Federated Learning—0
FedSat: A Statistical Aggregation Approach for Class Imbalanced Clients in Federated Learning—0
FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning—0
FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation—0
FedSKD: Aggregation-free Model-heterogeneous Federated Learning using Multi-dimensional Similarity Knowledge Distillation—0
FedSmart: An Auto Updating Federated Learning Optimization Mechanism—0
FedSpaLLM: Federated Pruning of Large Language Models—0
FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation—0
FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning—0
FedST: Secure Federated Shapelet Transformation for Time Series Classification—0
FedSyn: Synthetic Data Generation using Federated Learning—0
FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning—0
FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning—0
FedUD: Exploiting Unaligned Data for Cross-Platform Federated Click-Through Rate Prediction—0
FedVAE: Trajectory privacy preserving based on Federated Variational AutoEncoder—0
FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models—0
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data—0
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models—0
FedXGBoost: Privacy-Preserving XGBoost for Federated Learning—0
FedZeN: Towards superlinear zeroth-order federated learning via incremental Hessian estimation—0
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services—0
FeMLoc: Federated Meta-learning for Adaptive Wireless Indoor Localization Tasks in IoT Networks—0
Federated Learning with Heterogeneous Differential Privacy—0
Few-shot Image Recognition with Manifolds—0
FFA Sora, video generation as fundus fluorescein angiography simulator—0
FFConv: Fast Factorized Convolutional Neural Network Inference on Encrypted Data—0
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users—0
A methodology for training homomorphicencryption friendly neural networks—0
Fine-Tuning a Local LLaMA-3 Large Language Model for Automated Privacy-Preserving Physician Letter Generation in Radiation Oncology—0
Fine-Tuning Foundation Models with Federated Learning for Privacy Preserving Medical Time Series Forecasting—0
Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search—0
Finite-Time Analysis of Fully Decentralized Single-Timescale Actor-Critic—0
Finite Time Privacy Preserving Quantized Average Consensus with Transmission Stopping—0
First-Person Fairness in Chatbots—0
FLaaS: Federated Learning as a Service—0
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework—0
FLIGAN: Enhancing Federated Learning with Incomplete Data using GAN—0
Privacy-Preserving Federated Learning via Dataset Distillation—0
FLMarket: Enabling Privacy-preserved Pre-training Data Pricing for Federated Learning—0
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models—0
FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps—0
FLVoogd: Robust And Privacy Preserving Federated Learning—0
FOCUS: Dealing with Label Quality Disparity in Federated Learning—0
Fog Intelligence for Network Anomaly Detection—0
Forecasting Anonymized Electricity Load Profiles—0
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