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 4026–4050 of 6771 papers

Title	Date	Tasks	Status	Hype
Scalable Hierarchical Over-the-Air Federated Learning	Nov 29, 2022	Federated Learning	—Unverified	0
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing	Nov 28, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	0
AquaFeL-PSO: A Monitoring System for Water Resources using Autonomous Surface Vehicles based on Multimodal PSO and Federated Learning	Nov 28, 2022	Federated Learning	—Unverified	0
Federated Learning for 5G Base Station Traffic Forecasting	Nov 28, 2022	Federated LearningManagement	CodeCode Available	1
Federated Learning Attacks and Defenses: A Survey	Nov 27, 2022	Federated LearningSurvey	—Unverified	0
Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning	Nov 27, 2022	Federated LearningNavigate	—Unverified	0
FedSysID: A Federated Approach to Sample-Efficient System Identification	Nov 25, 2022	Federated Learning	CodeCode Available	0
MDA: Availability-Aware Federated Learning Client Selection	Nov 25, 2022	Federated Learning	CodeCode Available	0
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression	Nov 25, 2022	Federated Learning	—Unverified	0
Inverse Feasibility in Over-the-Air Federated Learning	Nov 25, 2022	Federated Learning	—Unverified	0
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability	Nov 25, 2022	Federated Learning	CodeCode Available	1
Federated Learning Hyper-Parameter Tuning from a System Perspective	Nov 24, 2022	Federated Learning	CodeCode Available	0
Knowledge-Aware Federated Active Learning with Non-IID Data	Nov 24, 2022	Active LearningFederated Learning	CodeCode Available	1
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels	Nov 24, 2022	Federated LearningMedical Diagnosis	CodeCode Available	0
Multi-Job Intelligent Scheduling with Cross-Device Federated Learning	Nov 24, 2022	Bayesian OptimizationFairness	—Unverified	0
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders	Nov 24, 2022	Community DetectionFederated Learning	—Unverified	0
A Dynamic Weighted Federated Learning for Android Malware Classification	Nov 23, 2022	ClassificationFederated Learning	CodeCode Available	1
Event-Triggered Decentralized Federated Learning over Resource-Constrained Edge Devices	Nov 23, 2022	Federated Learning	—Unverified	0
Vertical Federated Learning: Concepts, Advances and Challenges	Nov 23, 2022	FairnessFederated Learning	—Unverified	0
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing	Nov 23, 2022	Federated LearningGraph Learning	CodeCode Available	1
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data	Nov 22, 2022	Data AugmentationFederated Learning	CodeCode Available	1
GitFL: Adaptive Asynchronous Federated Learning using Version Control	Nov 22, 2022	Federated LearningReinforcement Learning (RL)	—Unverified	0
Online Federated Learning via Non-Stationary Detection and Adaptation amidst Concept Drift	Nov 22, 2022	Federated Learning	—Unverified	0
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning	Nov 21, 2022	Federated LearningOut-of-Distribution Generalization	—Unverified	0
SPIN: Simulated Poisoning and Inversion Network for Federated Learning-Based 6G Vehicular Networks	Nov 21, 2022	Federated LearningGenerative Adversarial Network	—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