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 1451–1475 of 6771 papers

Title	Date	Tasks	Status	Hype
FedModule: A Modular Federated Learning Framework	Sep 7, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	2
Enhancing Quantum Security over Federated Learning via Post-Quantum Cryptography	Sep 6, 2024	Federated Learning	—Unverified	0
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression	Sep 6, 2024	Federated Learning	—Unverified	0
Active-Passive Federated Learning for Vertically Partitioned Multi-view Data	Sep 6, 2024	Federated LearningVertical Federated Learning	—Unverified	0
Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?	Sep 5, 2024	Federated Learning	—Unverified	0
Wind turbine condition monitoring based on intra- and inter-farm federated learning	Sep 5, 2024	Fault DetectionFederated Learning	CodeCode Available	0
FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain Recommendation	Sep 5, 2024	Contrastive LearningFederated Learning	CodeCode Available	0
VFLGAN-TS: Vertical Federated Learning-based Generative Adversarial Networks for Publication of Vertically Partitioned Time-Series Data	Sep 5, 2024	AttributeFederated Learning	—Unverified	0
Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA	Sep 4, 2024	Federated Learningparameter-efficient fine-tuning	—Unverified	0
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation	Sep 4, 2024	Contribution AssessmentFederated Learning	—Unverified	0
Buffer-based Gradient Projection for Continual Federated Learning	Sep 3, 2024	Federated LearningIncremental Learning	CodeCode Available	0
Personalized Federated Learning via Active Sampling	Sep 3, 2024	Federated LearningPersonalized Federated Learning	—Unverified	0
FedMinds: Privacy-Preserving Personalized Brain Visual Decoding	Sep 3, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Collaboratively Learning Federated Models from Noisy Decentralized Data	Sep 3, 2024	Federated Learning	—Unverified	0
Federated Prediction-Powered Inference from Decentralized Data	Sep 3, 2024	Federated LearningPrediction	CodeCode Available	0
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications	Sep 2, 2024	CPUFederated Learning	CodeCode Available	2
Fed-MUnet: Multi-modal Federated Unet for Brain Tumor Segmentation	Sep 2, 2024	Brain Tumor SegmentationFederated Learning	CodeCode Available	1
Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation	Sep 2, 2024	Federated Learning	CodeCode Available	0
GAS: Generative Activation-Aided Asynchronous Split Federated Learning	Sep 2, 2024	Federated Learning	CodeCode Available	0
MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning	Sep 2, 2024	Federated LearningMortality Prediction	CodeCode Available	0
Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness	Sep 1, 2024	Decision MakingFederated Learning	—Unverified	0
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism	Sep 1, 2024	Bayesian OptimizationEvent Detection	CodeCode Available	0
Demo: FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics	Aug 31, 2024	Federated LearningPrivacy Preserving	CodeCode Available	0
Towards Hyper-parameter-free Federated Learning	Aug 30, 2024	Federated Learning	CodeCode Available	0
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition	Aug 30, 2024	DecoderFederated Learning	CodeCode Available	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