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 2026–2050 of 6771 papers

Title	Date	Tasks	Status
Evaluating Multi-Global Server Architecture for Federated Learning	Nov 26, 2023	Federated Learning	—Unverified
Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning	Dec 19, 2022	Federated Learning	—Unverified
Evaluating the Communication Efficiency in Federated Learning Algorithms	Apr 6, 2020	Federated Learningspeech-recognition	—Unverified
Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction	Dec 10, 2024	Disease PredictionFederated Learning	—Unverified
Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated Learning	May 26, 2023	Federated LearningPrivacy Preserving	—Unverified
Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach	Feb 16, 2024	Federated Learning	—Unverified
Fairness in Federated Learning for Spatial-Temporal Applications	Jan 17, 2022	FairnessFederated Learning	—Unverified
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation	Dec 10, 2023	Federated LearningKnowledge Distillation	—Unverified
Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System	Oct 15, 2021	Bayesian OptimizationFederated Learning	—Unverified
Event-Driven Online Vertical Federated Learning	Jun 17, 2025	Federated LearningVertical Federated Learning	—Unverified
Event-Triggered Decentralized Federated Learning over Resource-Constrained Edge Devices	Nov 23, 2022	Federated Learning	—Unverified
Evidential Federated Learning for Skin Lesion Image Classification	Nov 15, 2024	ClassificationFederated Learning	—Unverified
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning	Nov 13, 2023	Federated Learning	—Unverified
Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving	Sep 29, 2024	Autonomous DrivingFederated Learning	—Unverified
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning	Aug 19, 2021	Federated Learning	—Unverified
Cross-Silo Federated Learning: Challenges and Opportunities	Jun 26, 2022	Federated Learning	—Unverified
Exact Support Recovery in Federated Regression with One-shot Communication	Jun 22, 2020	Distributed ComputingFederated Learning	—Unverified
A Systematic Literature Review on Client Selection in Federated Learning	Jun 8, 2023	FairnessFederated Learning	—Unverified
ExclaveFL: Providing Transparency to Federated Learning using Exclaves	Dec 13, 2024	Federated Learning	—Unverified
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements	Dec 18, 2018	Federated Learning	—Unverified
Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression	Feb 6, 2024	Federated LearningModel Compression	—Unverified
A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles	Mar 10, 2022	Federated LearningSurvey	—Unverified
Adaptive Coded Federated Learning: Privacy Preservation and Straggler Mitigation	Mar 22, 2024	Federated Learning	—Unverified
Cross-Modal Vertical Federated Learning for MRI Reconstruction	Jun 5, 2023	DisentanglementFederated Learning	—Unverified
Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modality	Jan 25, 2024	cross-modal alignmentFederated Learning	—Unverified

Show:10 25 50

← PrevPage 82 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