SOTAVerified

Federated Learning

Federated Learning is a machine learning approach that allows multiple devices or entities to collaboratively train a shared model without exchanging their data with each other. Instead of sending data to a central server for training, the model is trained locally on each device, and only the model updates are sent to the central server, where they are aggregated to improve the shared model.

This approach allows for privacy-preserving machine learning, as each device keeps its data locally and only shares the information needed to improve the model.

Papers

Showing 751800 of 6771 papers

TitleStatusHype
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated LearningCode1
FedCorr: Multi-Stage Federated Learning for Label Noise CorrectionCode1
FedCV: A Federated Learning Framework for Diverse Computer Vision TasksCode1
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID DataCode1
FedLesScan: Mitigating Stragglers in Serverless Federated LearningCode1
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and CorrectionCode1
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation LearningCode1
PFA: Privacy-preserving Federated Adaptation for Effective Model PersonalizationCode1
FedMix: Mixed Supervised Federated Learning for Medical Image SegmentationCode1
FedDefender: Backdoor Attack Defense in Federated LearningCode1
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental RegularizationCode1
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency SpaceCode1
FedBE: Making Bayesian Model Ensemble Applicable to Federated LearningCode1
FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous DrivingCode1
FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous DrivingCode1
Physics-Driven Spectrum-Consistent Federated Learning for Palmprint VerificationCode1
Federated Bayesian Optimization via Thompson SamplingCode1
Federated Adversarial Debiasing for Fair and Transferable RepresentationsCode1
Federated Learning with Label Distribution Skew via Logits CalibrationCode1
Power Allocation for Wireless Federated Learning using Graph Neural NetworksCode1
PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental LearningCode1
Federated Class-Incremental Learning with New-Class Augmented Self-DistillationCode1
Federated Composite OptimizationCode1
Practical Defences Against Model Inversion Attacks for Split Neural NetworksCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
ARFED: Attack-Resistant Federated averaging based on outlier eliminationCode1
Federated Deep Learning Meets Autonomous Vehicle Perception: Design and VerificationCode1
Federated Cross Learning for Medical Image SegmentationCode1
Fed-TDA: Federated Tabular Data Augmentation on Non-IID DataCode1
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless NetworksCode1
Federated Domain Generalization for Image Recognition via Cross-Client Style TransferCode1
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning BetterCode1
ALI-DPFL: Differentially Private Federated Learning with Adaptive Local IterationsCode1
Federated Learning-based Vehicle Trajectory Prediction against CyberattacksCode1
Federated Few-shot LearningCode1
FwdLLM: Efficient FedLLM using Forward GradientCode1
A Better Alternative to Error Feedback for Communication-Efficient Distributed LearningCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 KilobytesCode1
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient DescentCode1
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive TrainingCode1
Projected Federated Averaging with Heterogeneous Differential PrivacyCode1
Federated Incremental Semantic SegmentationCode1
Federated Knowledge DistillationCode1
Improving Generalization in Federated Learning by Seeking Flat MinimaCode1
Bayesian Framework for Gradient LeakageCode1
Federated Learning Based on Dynamic RegularizationCode1
TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron ProvenanceCode1
Federated Learning for Computational Pathology on Gigapixel Whole Slide ImagesCode1
Post Quantum Secure Blockchain-based Federated Learning for Mobile Edge ComputingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SiloBN + ASAMmIoU49.75Unverified
2SiloBN + SAMmIoU49.1Unverified
3SiloBNmIoU45.96Unverified
4FedSAM + SWAmIoU43.42Unverified
5FedASAM + SWAmIoU43.02Unverified
6FedAvg + SWAmIoU42.48Unverified
7FedASAMmIoU42.27Unverified
8FedSAMmIoU41.22Unverified
9FedAvgmIoU38.65Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAAcc@1-1262Clients68.32Unverified
2FedSAM + SWAAcc@1-1262Clients68.12Unverified
3FedAvg + SWAAcc@1-1262Clients67.52Unverified
4FedASAMAcc@1-1262Clients64.23Unverified
5FedSAMAcc@1-1262Clients63.72Unverified
6FedAvgAcc@1-1262Clients61.91Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients42.64Unverified
2FedASAMACC@1-100Clients39.76Unverified
3FedSAM + SWAACC@1-100Clients39.51Unverified
4FedSAMACC@1-100Clients36.93Unverified
5FedAvgACC@1-100Clients36.74Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients41.62Unverified
2FedASAMACC@1-100Clients40.81Unverified
3FedSAM + SWAACC@1-100Clients39.24Unverified
4FedAvgACC@1-100Clients38.59Unverified
5FedSAMACC@1-100Clients38.56Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients48.72Unverified
2FedSAM + SWAACC@1-100Clients46.76Unverified
3FedASAMACC@1-100Clients46.58Unverified
4FedSAMACC@1-100Clients44.84Unverified
5FedAvgACC@1-100Clients41.27Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients48.27Unverified
2FedASAMACC@1-100Clients47.78Unverified
3FedSAM + SWAACC@1-100Clients46.47Unverified
4FedSAMACC@1-100Clients46.05Unverified
5FedAvgACC@1-100Clients42.17Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients49.17Unverified
2FedSAM + SWAACC@1-100Clients47.96Unverified
3FedASAMACC@1-100Clients45.61Unverified
4FedSAMACC@1-100Clients44.73Unverified
5FedAvgACC@1-100Clients40.43Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients42.01Unverified
2FedSAM + SWAACC@1-100Clients39.3Unverified
3FedASAMACC@1-100Clients36.04Unverified
4FedSAMACC@1-100Clients31.04Unverified
5FedAvgACC@1-100Clients30.25Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.97Unverified
2FedASAM + SWAACC@1-100Clients54.79Unverified
3FedSAM + SWAACC@1-100Clients53.67Unverified
4FedSAMACC@1-100Clients53.39Unverified
5FedAvgACC@1-100Clients50.25Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.5Unverified
2FedSAM + SWAACC@1-100Clients54.36Unverified
3FedASAM + SWAACC@1-100Clients54.1Unverified
4FedSAMACC@1-100Clients53.97Unverified
5FedAvgACC@1-100Clients50.66Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.81Unverified
2FedSAMACC@1-100Clients54.01Unverified
3FedSAM + SWAACC@1-100Clients53.9Unverified
4FedASAM + SWAACC@1-100Clients53.86Unverified
5FedAvgACC@1-100Clients49.92Unverified
#ModelMetricClaimedVerifiedStatus
1AdaBestAverage Top-1 Accuracy56.2Unverified