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 2151–2175 of 6771 papers

Title	Date	Tasks	Status	Hype
Adaptive Decentralized Federated Learning in Energy and Latency Constrained Wireless Networks	Mar 29, 2024	Federated Learning	—Unverified	0
Biased Over-the-Air Federated Learning under Wireless Heterogeneity	Mar 28, 2024	Federated Learning	—Unverified	0
Client-supervised Federated Learning: Towards One-model-for-all Personalization	Mar 28, 2024	AllFederated Learning	—Unverified	0
Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning	Mar 28, 2024	Distributed ComputingFederated Learning	—Unverified	0
Dual-Personalizing Adapter for Federated Foundation Models	Mar 28, 2024	Federated Learning	CodeCode Available	1
Generalized Policy Learning for Smart Grids: FL TRPO Approach	Mar 27, 2024	energy managementFederated Learning	—Unverified	0
Stragglers-Aware Low-Latency Synchronous Federated Learning via Layer-Wise Model Updates	Mar 27, 2024	Federated Learning	CodeCode Available	0
Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices	Mar 27, 2024	Federated Learning	—Unverified	0
FRESCO: Federated Reinforcement Energy System for Cooperative Optimization	Mar 27, 2024	Federated Learning	—Unverified	0
CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT	Mar 27, 2024	Federated LearningRepresentation Learning	—Unverified	0
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning	Mar 26, 2024	Federated Learning	—Unverified	0
Enhancing Privacy in Federated Learning through Local Training	Mar 26, 2024	Federated Learning	—Unverified	0
Empowering Data Mesh with Federated Learning	Mar 26, 2024	Decision MakingFederated Learning	CodeCode Available	0
Secure Aggregation is Not Private Against Membership Inference Attacks	Mar 26, 2024	Federated LearningPrivacy Preserving	CodeCode Available	0
Not All Federated Learning Algorithms Are Created Equal: A Performance Evaluation Study	Mar 26, 2024	AllFederated Learning	—Unverified	0
GPFL: A Gradient Projection-Based Client Selection Framework for Efficient Federated Learning	Mar 26, 2024	Federated Learning	—Unverified	0
FLIGAN: Enhancing Federated Learning with Incomplete Data using GAN	Mar 25, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Distributed collaborative anomalous sound detection by embedding sharing	Mar 25, 2024	Federated Learning	—Unverified	0
Differentially Private Online Federated Learning with Correlated Noise	Mar 25, 2024	Federated Learning	—Unverified	0
Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients	Mar 25, 2024	Federated Learning	—Unverified	0
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning	Mar 25, 2024	Federated Learning	—Unverified	0
FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data	Mar 25, 2024	Dimensionality ReductionFederated Learning	—Unverified	0
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data	Mar 25, 2024	Federated LearningFederated Unsupervised Learning	—Unverified	0
Heterogeneous Federated Learning with Splited Language Model	Mar 24, 2024	Federated LearningLanguage Modeling	—Unverified	0
A Federated Parameter Aggregation Method for Node Classification Tasks with Different Graph Network Structures	Mar 24, 2024	Federated LearningGraph Neural 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