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 1651–1675 of 6771 papers

Title	Date	Tasks	Status	Hype
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging	Jul 11, 2024	DiversityFederated Learning	CodeCode Available	1
CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities	Jul 11, 2024	Data AugmentationFederated Learning	CodeCode Available	1
Federated Learning and AI Regulation in the European Union: Who is Responsible? -- An Interdisciplinary Analysis	Jul 11, 2024	Federated Learning	—Unverified	0
Distributed Deep Reinforcement Learning Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing	Jul 11, 2024	Deep Reinforcement LearningEdge-computing	—Unverified	0
FedLog: Personalized Federated Classification with Less Communication and More Flexibility	Jul 11, 2024	Bayesian InferenceFederated Learning	—Unverified	0
Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language Models (Extended Version)	Jul 11, 2024	Federated LearningPrivacy Preserving	CodeCode Available	0
Feature Diversification and Adaptation for Federated Domain Generalization	Jul 11, 2024	Domain GeneralizationFederated Learning	—Unverified	0
FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels	Jul 10, 2024	Federated LearningPrivacy Preserving	CodeCode Available	0
Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging	Jul 10, 2024	Federated LearningPartially Labeled Datasets	CodeCode Available	0
FedClust: Tackling Data Heterogeneity in Federated Learning through Weight-Driven Client Clustering	Jul 9, 2024	Federated Learning	—Unverified	0
Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning	Jul 9, 2024	Federated Learning	—Unverified	0
A Differentially Private Blockchain-Based Approach for Vertical Federated Learning	Jul 9, 2024	Federated LearningVertical Federated Learning	CodeCode Available	0
Stabilized Proximal-Point Methods for Federated Optimization	Jul 9, 2024	Federated Learning	CodeCode Available	0
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory	Jul 9, 2024	Federated Learningparameter estimation	—Unverified	0
Threats and Defenses in Federated Learning Life Cycle: A Comprehensive Survey and Challenges	Jul 9, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Trust and Resilience in Federated Learning Through Smart Contracts Enabled Decentralized Systems	Jul 9, 2024	Federated Learning	—Unverified	0
A Survey on LoRA of Large Language Models	Jul 8, 2024	Federated Learningparameter-efficient fine-tuning	CodeCode Available	3
A Trustworthy AIoT-enabled Localization System via Federated Learning and Blockchain	Jul 8, 2024	Federated LearningIndoor Localization	—Unverified	0
FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging	Jul 8, 2024	Deep Reinforcement LearningFairness	CodeCode Available	0
Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients	Jul 7, 2024	Federated LearningKnowledge Distillation	—Unverified	0
Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion	Jul 7, 2024	DenoisingFederated Learning	—Unverified	0
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients	Jul 6, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Impact of Network Topology on Byzantine Resilience in Decentralized Federated Learning	Jul 6, 2024	Federated Learning	CodeCode Available	0
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning	Jul 6, 2024	Federated Learningimage-classification	CodeCode Available	0
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning	Jul 6, 2024	Federated 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