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 2101–2125 of 6771 papers

Title	Date	Tasks	Status
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays	May 16, 2024	Federated LearningStochastic Optimization	—Unverified
A Framework for Privacy-Preserving in IoV Using Federated Learning With Differential Privacy	Dec 9, 2024	Federated LearningPrivacy Preserving	—Unverified
A Privacy-Preserving Federated Learning Framework for Generalizable CBCT to Synthetic CT Translation in Head and Neck	Jun 10, 2025	Federated LearningGenerative Adversarial Network	—Unverified
FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation	Jun 3, 2024	Deep LearningFederated Learning	—Unverified
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning	May 15, 2023	Federated LearningPrivacy Preserving	—Unverified
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness	Sep 20, 2024	Federated LearningQuantization	—Unverified
CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT	Mar 27, 2024	Federated LearningRepresentation Learning	—Unverified
A Framework for Incentivized Collaborative Learning	May 26, 2023	Federated Learning	—Unverified
CopRA: A Progressive LoRA Training Strategy	Oct 30, 2024	Federated LearningLinear Mode Connectivity	—Unverified
Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity	Dec 7, 2023	Edge-computingFederated Learning	—Unverified
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise	Jul 17, 2020	Federated Learning	—Unverified
Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity	Jan 1, 2023	Federated Learning	—Unverified
Coordinated Replay Sample Selection for Continual Federated Learning	Oct 23, 2023	Continual LearningFederated Learning	—Unverified
Coordinated Attacks Against Federated Learning: A Multi-Agent Reinforcement Learning Approach	Sep 29, 2021	Federated LearningMulti-agent Reinforcement Learning	—Unverified
Asynchronous Federated Learning with Incentive Mechanism Based on Contract Theory	Oct 10, 2023	Federated Learning	—Unverified
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging	Jun 1, 2023	Federated LearningPrompt Learning	—Unverified
Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading	Dec 23, 2023	Federated LearningManagement	—Unverified
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation	Aug 1, 2023	Federated LearningQuantization	—Unverified
A Framework for Exploring Federated Community Detection	Dec 14, 2023	Community DetectionFederated Learning	—Unverified
FedADC: Accelerated Federated Learning with Drift Control	Dec 16, 2020	Federated Learning	—Unverified
Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning	Jan 16, 2025	Backdoor AttackFederated Learning	—Unverified
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence	Dec 17, 2019	Edge-computingFederated Learning	—Unverified
Supplementary File: Cooperative Gradient Coding for Semi-Decentralized Federated Learning	Mar 31, 2024	Federated Learningvalid	—Unverified
Cooperation and Personalization on a Seesaw: Choice-based FL for Safe Cooperation in Wireless Networks	Nov 6, 2024	FairnessFederated Learning	—Unverified
Asynchronous Federated Learning for Sensor Data with Concept Drift	Sep 1, 2021	Drift DetectionEnsemble Learning	—Unverified

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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