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 5601–5625 of 6771 papers

Title	Date	Tasks	Status	Hype
Personalized Federated Learning over non-IID Data for Indoor Localization	Jul 9, 2021	Federated LearningIndoor Localization	—Unverified	0
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform	Jul 8, 2021	BIG-bench Machine LearningBinary Classification	CodeCode Available	1
Federated Learning as a Mean-Field Game	Jul 8, 2021	Federated LearningPrivacy Preserving	—Unverified	0
Federated Model Search via Reinforcement Learning	Jul 7, 2021	Federated LearningImage Classification	—Unverified	0
Federated Learning with Downlink Device Selection	Jul 7, 2021	Federated Learningimage-classification	—Unverified	0
Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease	Jul 7, 2021	Action RecognitionData Augmentation	CodeCode Available	1
DER Forecast using Privacy Preserving Federated Learning	Jul 7, 2021	Federated LearningPrediction	—Unverified	0
Management of Resource at the Network Edge for Federated Learning	Jul 7, 2021	Federated LearningManagement	—Unverified	0
RoFL: Robustness of Secure Federated Learning	Jul 7, 2021	Federated LearningPrivacy Preserving	CodeCode Available	1
Energy Efficient Federated Learning in Integrated Fog-Cloud Computing Enabled Internet-of-Things Networks	Jul 7, 2021	Cloud ComputingFederated Learning	—Unverified	0
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging	Jul 6, 2021	Binary ClassificationFederated Learning	CodeCode Available	1
Differentially private federated deep learning for multi-site medical image segmentation	Jul 6, 2021	Deep LearningFederated Learning	CodeCode Available	0
Memory-aware curriculum federated learning for breast cancer classification	Jul 6, 2021	Breast Cancer DetectionCancer Classification	CodeCode Available	0
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy	Jul 5, 2021	Federated Learning	CodeCode Available	0
FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems	Jul 4, 2021	Federated Learning	—Unverified	0
Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning	Jul 4, 2021	Federated LearningScheduling	—Unverified	0
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates	Jul 3, 2021	Federated Learning	—Unverified	0
Segmented Federated Learning for Adaptive Intrusion Detection System	Jul 2, 2021	Federated LearningIntrusion Detection	—Unverified	0
Gradient-Leakage Resilient Federated Learning	Jul 2, 2021	Federated LearningPrivacy Preserving	CodeCode Available	1
On Bridging Generic and Personalized Federated Learning for Image Classification	Jul 2, 2021	ClassificationFederated Learning	CodeCode Available	1
FedCMR: Federated Cross-Modal Retrieval	Jul 1, 2021	Cross-Modal RetrievalFederated Learning	CodeCode Available	1
FedMix: Approximation of Mixup under Mean Augmented Federated Learning	Jul 1, 2021	Data AugmentationFederated Learning	CodeCode Available	1
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data	Jun 30, 2021	Federated LearningKnowledge Distillation	—Unverified	0
Faithful Edge Federated Learning: Scalability and Privacy	Jun 30, 2021	Federated Learning	—Unverified	0
UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach	Jun 29, 2021	Decision MakingDeep Reinforcement Learning	—Unverified	0

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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