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 226–250 of 6771 papers

Title	Date	Tasks	Status	Hype
FLTracer: Accurate Poisoning Attack Provenance in Federated Learning	Oct 20, 2023	Anomaly DetectionFederated Learning	CodeCode Available	1
Passive Inference Attacks on Split Learning via Adversarial Regularization	Oct 16, 2023	Federated Learning	CodeCode Available	1
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning	Oct 15, 2023	Federated LearningVertical Federated Learning	CodeCode Available	1
Sample-Driven Federated Learning for Energy-Efficient and Real-Time IoT Sensing	Oct 11, 2023	Federated Learning	CodeCode Available	1
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning	Oct 8, 2023	Federated Learning	CodeCode Available	1
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning	Oct 6, 2023	Federated Learning	CodeCode Available	1
On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond	Oct 4, 2023	DiversityFederated Learning	CodeCode Available	1
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things	Sep 29, 2023	BenchmarkingFederated Learning	CodeCode Available	1
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective	Sep 28, 2023	Federated Learning	CodeCode Available	1
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning	Sep 28, 2023	Domain GeneralizationFederated Learning	CodeCode Available	1
A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets	Sep 28, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available	1
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler	Sep 26, 2023	Federated Learning	CodeCode Available	1
FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous Driving	Sep 23, 2023	Autonomous DrivingDomain Generalization	CodeCode Available	1
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training	Sep 21, 2023	backdoor defenseDistributed Computing	CodeCode Available	1
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training	Sep 21, 2023	backdoor defenseDistributed Computing	CodeCode Available	1
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration	Sep 20, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available	1
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks	Sep 19, 2023	Federated LearningPrediction	CodeCode Available	1
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning	Sep 15, 2023	Data AugmentationDisentanglement	CodeCode Available	1
FedJudge: Federated Legal Large Language Model	Sep 15, 2023	Continual LearningFederated Learning	CodeCode Available	1
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization	Sep 13, 2023	Federated Learning	CodeCode Available	1
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning	Sep 11, 2023	Federated Learningimage-classification	CodeCode Available	1
Bias Propagation in Federated Learning	Sep 5, 2023	FairnessFederated Learning	CodeCode Available	1
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment	Aug 31, 2023	Federated LearningLesion Classification	CodeCode Available	1
CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot Interaction	Aug 29, 2023	Federated Learningimage-classification	CodeCode Available	1
FwdLLM: Efficient FedLLM using Forward Gradient	Aug 26, 2023	Federated Learning	CodeCode Available	1

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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