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 501–525 of 6771 papers

Title	Date	Tasks	Status	Hype
Semantic Communication in Dynamic Channel Scenarios: Collaborative Optimization of Dual-Pipeline Joint Source-Channel Coding and Personalized Federated Learning	Mar 18, 2025	Federated LearningPersonalized Federated Learning	—Unverified	0
Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions	Mar 17, 2025	Federated Learning	CodeCode Available	0
Federated Learning with Domain Shift Eraser	Mar 17, 2025	Federated Learning	—Unverified	0
Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning	Mar 17, 2025	Federated Learning	—Unverified	0
A Linearized Alternating Direction Multiplier Method for Federated Matrix Completion Problems	Mar 17, 2025	Computational EfficiencyFederated Learning	—Unverified	0
Federated Continual Instruction Tuning	Mar 17, 2025	Federated Learning	—Unverified	0
Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch	Mar 17, 2025	Federated LearningPseudo Label	CodeCode Available	1
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation	Mar 17, 2025	Federated LearningPrivacy Preserving	—Unverified	0
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning	Mar 17, 2025	Federated Learning	CodeCode Available	0
GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation	Mar 17, 2025	Federated LearningImage Classification	—Unverified	0
FedVSR: Towards Model-Agnostic Federated Learning in Video Super-Resolution	Mar 17, 2025	Federated LearningFederated Learning (Video Super-Resolution)	CodeCode Available	1
FedGAI: Federated Style Learning with Cloud-Edge Collaboration for Generative AI in Fashion Design	Mar 16, 2025	Federated Learning	—Unverified	0
Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning	Mar 16, 2025	Federated LearningPrivacy Preserving	—Unverified	0
Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning	Mar 16, 2025	Federated LearningLarge Language Model	—Unverified	0
XAI-Driven Client Selection for Federated Learning in Scalable 6G Network Slicing	Mar 16, 2025	Federated Learning	—Unverified	0
A State Alignment-Centric Approach to Federated System Identification: The FedAlign Framework	Mar 15, 2025	Federated LearningState Space Models	—Unverified	0
FedTilt: Towards Multi-Level Fairness-Preserving and Robust Federated Learning	Mar 15, 2025	FairnessFederated Learning	—Unverified	0
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data	Mar 15, 2025	Demand ForecastingFeature Importance	—Unverified	0
Research on Large Language Model Cross-Cloud Privacy Protection and Collaborative Training based on Federated Learning	Mar 15, 2025	Cloud ComputingFederated Learning	—Unverified	0
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective	Mar 15, 2025	Federated LearningImputation	—Unverified	0
A Survey on Federated Fine-tuning of Large Language Models	Mar 15, 2025	Federated Learningparameter-efficient fine-tuning	CodeCode Available	2
Federated Learning for Secure and Efficient Device Activity Detection in mMTC Networks	Mar 14, 2025	Action DetectionActivity Detection	—Unverified	0
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning	Mar 14, 2025	Federated Learning	—Unverified	0
Performance Analysis of Decentralized Federated Learning Deployments	Mar 14, 2025	Federated Learning	—Unverified	0
Enabling Weak Client Participation via On-device Knowledge Distillation in Heterogenous Federated Learning	Mar 14, 2025	Federated LearningKnowledge Distillation	—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