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 976–1000 of 6771 papers

Title	Date	Tasks	Status	Hype
Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction	Dec 10, 2024	Disease PredictionFederated Learning	—Unverified	0
How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?	Dec 10, 2024	Federated Learning	—Unverified	0
Optimizing Personalized Federated Learning through Adaptive Layer-Wise Learning	Dec 10, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	1
A New Federated Learning Framework Against Gradient Inversion Attacks	Dec 10, 2024	Federated LearningPrivacy Preserving	CodeCode Available	1
Hierarchical Split Federated Learning: Convergence Analysis and System Optimization	Dec 10, 2024	Federated Learning	—Unverified	0
Learnable Sparse Customization in Heterogeneous Edge Computing	Dec 10, 2024	Edge-computingFederated Learning	CodeCode Available	0
Latency Minimization for UAV-Enabled Federated Learning: Trajectory Design and Resource Allocation	Dec 10, 2024	Federated Learning	—Unverified	0
Privacy-Preserving Customer Support: A Framework for Secure and Scalable Interactions	Dec 10, 2024	Federated LearningInformation Retrieval	—Unverified	0
Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning	Dec 10, 2024	Computational EfficiencyFederated Learning	—Unverified	0
A Framework for Privacy-Preserving in IoV Using Federated Learning With Differential Privacy	Dec 9, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Sequential Compression Layers for Efficient Federated Learning in Foundational Models	Dec 9, 2024	Federated Learningparameter-efficient fine-tuning	—Unverified	0
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications	Dec 9, 2024	Federated Learning	—Unverified	0
FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesis	Dec 9, 2024	Federated LearningSSIM	—Unverified	0
H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications	Dec 9, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Federated Split Learning with Model Pruning and Gradient Quantization in Wireless Networks	Dec 9, 2024	Federated LearningQuantization	—Unverified	0
Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions	Dec 9, 2024	Federated LearningPrivacy Preserving	—Unverified	0
FedRBE -- a decentralized privacy-preserving federated batch effect correction tool for omics data based on limma	Dec 8, 2024	Federated LearningMissing Values	—Unverified	0
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices	Dec 8, 2024	Edge-computingFederated Learning	CodeCode Available	1
Upcycling Noise for Federated Unlearning	Dec 7, 2024	Federated Learning	—Unverified	0
One-shot Federated Learning via Synthetic Distiller-Distillate Communication	Dec 6, 2024	Data-free Knowledge DistillationFederated Learning	CodeCode Available	1
NebulaFL: Effective Asynchronous Federated Learning for JointCloud Computing	Dec 6, 2024	Federated LearningScheduling	—Unverified	0
Privacy Drift: Evolving Privacy Concerns in Incremental Learning	Dec 6, 2024	Federated LearningIncremental Learning	—Unverified	0
A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communities	Dec 6, 2024	Federated LearningFew-Shot Learning	—Unverified	0
Communication Compression for Distributed Learning without Control Variates	Dec 5, 2024	Federated LearningPrivacy Preserving	—Unverified	0
FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning	Dec 5, 2024	Federated LearningKnowledge Distillation	CodeCode Available	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