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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1326–1350 of 6771 papers

Title	Date	Tasks	Status	Score
Federated Learning for Data Streams	Jan 4, 2023	Federated Learning	CodeCode Available	5
A Survey on Contribution Evaluation in Vertical Federated Learning	May 3, 2024	Federated LearningSurvey	CodeCode Available	5
Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations	May 25, 2024	Decision MakingEpidemiology	CodeCode Available	5
Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks	Dec 9, 2020	BIG-bench Machine LearningFederated Learning	CodeCode Available	5
Federated Learning based on Pruning and Recovery	Mar 16, 2024	Federated Learning	CodeCode Available	5
Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling	Sep 7, 2021	Federated Learning	CodeCode Available	5
Federated Learning Based Multilingual Emoji Prediction In Clean and Attack Scenarios	Mar 30, 2023	Federated LearningPrediction	CodeCode Available	5
Federated Learning Client Pruning for Noisy Labels	Nov 11, 2024	Federated Learning	CodeCode Available	5
Federated Intelligence for Active Queue Management in Inter-Domain Congestion	Jan 8, 2021	Federated LearningManagement	CodeCode Available	5
Federated Impression for Learning with Distributed Heterogeneous Data	Sep 11, 2024	Federated Learning	CodeCode Available	5
Federated Hypergradient Descent	Nov 3, 2022	Federated LearningHyperparameter Optimization	CodeCode Available	5
Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data	Apr 26, 2024	ECG ClassificationFederated Learning	CodeCode Available	5
FedHIL: Heterogeneity Resilient Federated Learning for Robust Indoor Localization with Mobile Devices	Jul 4, 2023	Federated LearningIndoor Localization	CodeCode Available	5
Federated learning compression designed for lightweight communications	Oct 23, 2023	Cloud ComputingFederated Learning	CodeCode Available	5
Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging	Jul 10, 2024	Federated LearningPartially Labeled Datasets	CodeCode Available	5
Federated Frank-Wolfe Algorithm	Aug 19, 2024	Federated LearningPrivacy Preserving	CodeCode Available	5
Federated f-Differential Privacy	Feb 22, 2021	Federated Learning	CodeCode Available	5
Federated Few-shot Learning for Cough Classification with Edge Devices	Sep 3, 2023	Cough ClassificationFederated Learning	CodeCode Available	5
Federated Face Forgery Detection Learning with Personalized Representation	Jun 17, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	5
Federated Fairness Analytics: Quantifying Fairness in Federated Learning	Aug 15, 2024	FairnessFederated Learning	CodeCode Available	5
Federated Graph Learning with Structure Proxy Alignment	Aug 18, 2024	Federated LearningFraud Detection	CodeCode Available	5
Federated Learning Meets Fairness and Differential Privacy	Aug 23, 2021	FairnessFederated Learning	CodeCode Available	5
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity	Feb 9, 2021	Federated Learning	CodeCode Available	5
Comparative Evaluation of Clustered Federated Learning Methods	Oct 18, 2024	Federated Learningimage-classification	CodeCode Available	5
A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration	Sep 29, 2023	Continual LearningFederated Learning	CodeCode Available	5

Show:10 25 50

← PrevPage 54 of 271Next →

All datasets Cityscapes heterogeneous Landmarks-User-160k CIFAR-100 (alpha=0, 10 clients per round)CIFAR-100 (alpha=0, 20 clients per round)CIFAR-100 (alpha=0.5, 10 clients per round)CIFAR-100 (alpha=0.5, 20 clients per round)CIFAR-100 (alpha=0.5, 5 clients per round)CIFAR-100 (alpha=0, 5 clients per round)CIFAR-100 (alpha=1000, 10 clients per round)CIFAR-100 (alpha=1000, 20 clients per round)CIFAR-100 (alpha=1000, 5 clients per round)CIFAR100 (alpha=0.3, 10 clients per round)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SiloBN + ASAM	mIoU	49.75	—	Unverified
2	SiloBN + SAM	mIoU	49.1	—	Unverified
3	SiloBN	mIoU	45.96	—	Unverified
4	FedSAM + SWA	mIoU	43.42	—	Unverified
5	FedASAM + SWA	mIoU	43.02	—	Unverified
6	FedAvg + SWA	mIoU	42.48	—	Unverified
7	FedASAM	mIoU	42.27	—	Unverified
8	FedSAM	mIoU	41.22	—	Unverified
9	FedAvg	mIoU	38.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	Acc@1-1262Clients	68.32	—	Unverified
2	FedSAM + SWA	Acc@1-1262Clients	68.12	—	Unverified
3	FedAvg + SWA	Acc@1-1262Clients	67.52	—	Unverified
4	FedASAM	Acc@1-1262Clients	64.23	—	Unverified
5	FedSAM	Acc@1-1262Clients	63.72	—	Unverified
6	FedAvg	Acc@1-1262Clients	61.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	42.64	—	Unverified
2	FedASAM	ACC@1-100Clients	39.76	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	39.51	—	Unverified
4	FedSAM	ACC@1-100Clients	36.93	—	Unverified
5	FedAvg	ACC@1-100Clients	36.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	41.62	—	Unverified
2	FedASAM	ACC@1-100Clients	40.81	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	39.24	—	Unverified
4	FedAvg	ACC@1-100Clients	38.59	—	Unverified
5	FedSAM	ACC@1-100Clients	38.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	48.72	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	46.76	—	Unverified
3	FedASAM	ACC@1-100Clients	46.58	—	Unverified
4	FedSAM	ACC@1-100Clients	44.84	—	Unverified
5	FedAvg	ACC@1-100Clients	41.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	48.27	—	Unverified
2	FedASAM	ACC@1-100Clients	47.78	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	46.47	—	Unverified
4	FedSAM	ACC@1-100Clients	46.05	—	Unverified
5	FedAvg	ACC@1-100Clients	42.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	49.17	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	47.96	—	Unverified
3	FedASAM	ACC@1-100Clients	45.61	—	Unverified
4	FedSAM	ACC@1-100Clients	44.73	—	Unverified
5	FedAvg	ACC@1-100Clients	40.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	42.01	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	39.3	—	Unverified
3	FedASAM	ACC@1-100Clients	36.04	—	Unverified
4	FedSAM	ACC@1-100Clients	31.04	—	Unverified
5	FedAvg	ACC@1-100Clients	30.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.97	—	Unverified
2	FedASAM + SWA	ACC@1-100Clients	54.79	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	53.67	—	Unverified
4	FedSAM	ACC@1-100Clients	53.39	—	Unverified
5	FedAvg	ACC@1-100Clients	50.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.5	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	54.36	—	Unverified
3	FedASAM + SWA	ACC@1-100Clients	54.1	—	Unverified
4	FedSAM	ACC@1-100Clients	53.97	—	Unverified
5	FedAvg	ACC@1-100Clients	50.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.81	—	Unverified
2	FedSAM	ACC@1-100Clients	54.01	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	53.9	—	Unverified
4	FedASAM + SWA	ACC@1-100Clients	53.86	—	Unverified
5	FedAvg	ACC@1-100Clients	49.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AdaBest	Average Top-1 Accuracy	56.2	—	Unverified