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 301350 of 6771 papers

TitleStatusHype
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of ThingsCode1
Evaluation Framework For Large-scale Federated LearningCode1
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a ServiceCode1
APPFL: Open-Source Software Framework for Privacy-Preserving Federated LearningCode1
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated LearningCode1
Exploiting Shared Representations for Personalized Federated LearningCode1
Backdoor Attacks on Federated Learning with Lottery Ticket HypothesisCode1
ARFED: Attack-Resistant Federated averaging based on outlier eliminationCode1
Applied Federated Learning: Improving Google Keyboard Query SuggestionsCode1
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated LearningCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State MatchingCode1
Fast Federated Learning by Balancing Communication Trade-OffsCode1
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine LearningCode1
Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class ImbalanceCode1
Fast Optimal Locally Private Mean Estimation via Random ProjectionsCode1
Fault-Tolerant Federated Reinforcement Learning with Theoretical GuaranteeCode1
Benchmarking Differential Privacy and Federated Learning for BERT ModelsCode1
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive MappingCode1
Masked Jigsaw Puzzle: A Versatile Position Embedding for Vision TransformersCode1
Adaptive and Parallel Split Federated Learning in Vehicular Edge ComputingCode1
A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge LearningCode1
Analysis and Evaluation of Synchronous and Asynchronous FLchainCode1
Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT ImagingCode1
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias ReductionCode1
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive CollaborationCode1
ByzFL: Research Framework for Robust Federated LearningCode1
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic SystemsCode1
A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime DetectionCode1
Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service DetectionCode1
Byzantine-Robust Decentralized Learning via ClippedGossipCode1
FedCD: Improving Performance in non-IID Federated LearningCode1
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy GuaranteesCode1
Omnidirectional Transfer for Quasilinear Lifelong LearningCode1
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated LearningCode1
CAFE: Catastrophic Data Leakage in Vertical Federated LearningCode1
Can Foundation Models Help Us Achieve Perfect Secrecy?Code1
Dopamine: Differentially Private Federated Learning on Medical DataCode1
CaPC Learning: Confidential and Private Collaborative LearningCode1
Can Textual Gradient Work in Federated Learning?Code1
CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing ModalitiesCode1
FedCMR: Federated Cross-Modal RetrievalCode1
Enhancing Efficiency in Multidevice Federated Learning through Data SelectionCode1
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian SamplingCode1
Dual-Personalizing Adapter for Federated Foundation ModelsCode1
FedCorr: Multi-Stage Federated Learning for Label Noise CorrectionCode1
Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical ImagingCode1
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept DriftCode1
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated LearningCode1
Dynamic Defense Against Byzantine Poisoning Attacks in Federated LearningCode1
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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