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 1926–1950 of 6771 papers

Title	Date	Tasks	Status	Hype
Federated Learning for Time-Series Healthcare Sensing with Incomplete Modalities	May 20, 2024	Computational EfficiencyFederated Learning	CodeCode Available	0
Securing Health Data on the Blockchain: A Differential Privacy and Federated Learning Framework	May 19, 2024	Federated Learning	—Unverified	0
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors	May 19, 2024	Domain AdaptationFederated Learning	CodeCode Available	1
The Future of Large Language Model Pre-training is Federated	May 17, 2024	Federated LearningLanguage Modeling	—Unverified	0
Federated Learning With Energy Harvesting Devices: An MDP Framework	May 17, 2024	Deep Reinforcement LearningFederated Learning	—Unverified	0
Cyclical Weight Consolidation: Towards Solving Catastrophic Forgetting in Serial Federated Learning	May 17, 2024	Federated Learning	—Unverified	0
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy	May 16, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Advances in Robust Federated Learning: Heterogeneity Considerations	May 16, 2024	DiversityFederated Learning	—Unverified	0
Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models	May 16, 2024	Federated Learning	CodeCode Available	0
Balancing Similarity and Complementarity for Federated Learning	May 16, 2024	Federated Learning	—Unverified	0
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective	May 16, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Federated Hybrid Model Pruning through Loss Landscape Exploration	May 16, 2024	Computational EfficiencyFederated Learning	CodeCode Available	0
Harmonizing Generalization and Personalization in Federated Prompt Learning	May 16, 2024	Federated LearningPrompt Learning	CodeCode Available	1
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays	May 16, 2024	Federated LearningStochastic Optimization	—Unverified	0
Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy	May 15, 2024	Federated Learningimage-classification	CodeCode Available	1
Dual-Segment Clustering Strategy for Hierarchical Federated Learning in Heterogeneous Wireless Environments	May 15, 2024	ClusteringFederated Learning	—Unverified	0
Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning	May 15, 2024	Federated Learning	—Unverified	0
SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning	May 15, 2024	Continual LearningFederated Learning	—Unverified	0
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain	May 15, 2024	Federated Learning	—Unverified	0
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises	May 14, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Differentially Private Federated Learning: A Systematic Review	May 14, 2024	Federated LearningPrivacy Preserving	—Unverified	0
Towards Energy-Aware Federated Learning via MARL: A Dual-Selection Approach for Model and Client	May 13, 2024	Federated Learning	—Unverified	0
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization	May 13, 2024	Distributed OptimizationFederated Learning	—Unverified	0
Mitigating federated learning contribution allocation instability through randomized aggregation	May 13, 2024	FairnessFederated Learning	—Unverified	0
Federated Hierarchical Tensor Networks: a Collaborative Learning Quantum AI-Driven Framework for Healthcare	May 13, 2024	Federated LearningTensor Networks	—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