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 1401–1425 of 6771 papers

Title	Date	Tasks	Status	Hype
SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework	Sep 20, 2024	Federated Learning	—Unverified	0
Boosting Federated Domain Generalization: Understanding the Role of Advanced Pre-Trained Architectures	Sep 20, 2024	Domain GeneralizationFederated Learning	—Unverified	0
Data Distribution Shifts in (Industrial) Federated Learning as a Privacy Issue	Sep 20, 2024	Federated Learning	—Unverified	0
On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists	Sep 20, 2024	Federated LearningLanguage Modeling	CodeCode Available	0
FedAT: Federated Adversarial Training for Distributed Insider Threat Detection	Sep 19, 2024	Federated Learning	—Unverified	0
The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning	Sep 19, 2024	Federated Learning	—Unverified	0
Green Federated Learning: A new era of Green Aware AI	Sep 19, 2024	Federated LearningNavigate	—Unverified	0
Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data	Sep 19, 2024	Computational EfficiencyFederated Learning	—Unverified	0
Communication-Efficient Federated Low-Rank Update Algorithm and its Connection to Implicit Regularization	Sep 19, 2024	Federated Learning	—Unverified	0
FedLF: Adaptive Logit Adjustment and Feature Optimization in Federated Long-Tailed Learning	Sep 18, 2024	Federated Learning	CodeCode Available	0
Promise and Peril of Collaborative Code Generation Models: Balancing Effectiveness and Memorization	Sep 18, 2024	Code GenerationFederated Learning	—Unverified	0
Enhancing Mental Health Support through Human-AI Collaboration: Toward Secure and Empathetic AI-enabled chatbots	Sep 17, 2024	ChatbotFederated Learning	—Unverified	0
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework	Sep 17, 2024	BenchmarkingFederated Learning	CodeCode Available	2
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction	Sep 17, 2024	Dimensionality ReductionFederated Learning	—Unverified	0
Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis	Sep 17, 2024	Federated Learning	—Unverified	0
A Green Multi-Attribute Client Selection for Over-The-Air Federated Learning: A Grey-Wolf-Optimizer Approach	Sep 16, 2024	AttributeFairness	—Unverified	0
Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities	Sep 16, 2024	Federated LearningSurvey	—Unverified	0
TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering	Sep 16, 2024	ClusteringFederated Learning	CodeCode Available	0
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare	Sep 15, 2024	Federated Learning	—Unverified	0
Federated Learning in Adversarial Environments: Testbed Design and Poisoning Resilience in Cybersecurity	Sep 15, 2024	Federated LearningIntrusion Detection	—Unverified	0
Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML	Sep 14, 2024	Federated LearningPrivacy Preserving	CodeCode Available	1
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks	Sep 14, 2024	Data-free Knowledge DistillationFederated Learning	—Unverified	0
Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learning	Sep 14, 2024	Bilevel OptimizationDistributed Computing	—Unverified	0
Enhancing Privacy in ControlNet and Stable Diffusion via Split Learning	Sep 13, 2024	Federated LearningImage Generation	—Unverified	0
FedProphet: Memory-Efficient Federated Adversarial Training via Theoretic-Robustness and Low-Inconsistency Cascade Learning	Sep 12, 2024	Adversarial RobustnessFederated Learning	—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