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 3401–3450 of 6771 papers

Title	Date	Tasks	Status
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization	Nov 2, 2023	Federated Learning	—Unverified
Federated Learning on Edge Sensing Devices: A Review	Nov 2, 2023	Federated Learning	—Unverified
FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks	Nov 2, 2023	Federated Learningimage-classification	—Unverified
StableFDG: Style and Attention Based Learning for Federated Domain Generalization	Nov 1, 2023	DiversityDomain Generalization	—Unverified
MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows	Nov 1, 2023	Federated LearningScheduling	—Unverified
A Comprehensive Study on Model Initialization Techniques Ensuring Efficient Federated Learning	Oct 31, 2023	Federated LearningPrivacy Preserving	—Unverified
Privacy-preserving design of graph neural networks with applications to vertical federated learning	Oct 31, 2023	Federated LearningGraph Representation Learning	—Unverified
FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments	Oct 31, 2023	Deep LearningFederated Learning	—Unverified
FedRec+: Enhancing Privacy and Addressing Heterogeneity in Federated Recommendation Systems	Oct 31, 2023	Federated LearningRecommendation Systems	—Unverified
Compression with Exact Error Distribution for Federated Learning	Oct 31, 2023	Federated Learning	—Unverified
Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection	Oct 30, 2023	Anomaly DetectionFederated Learning	—Unverified
Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning	Oct 30, 2023	Federated Learning	CodeCode Available
Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification	Oct 30, 2023	Federated LearningPrivacy Preserving	—Unverified
Enhancing Scalability and Reliability in Semi-Decentralized Federated Learning With Blockchain: Trust Penalization and Asynchronous Functionality	Oct 30, 2023	Federated Learning	—Unverified
PriPrune: Quantifying and Preserving Privacy in Pruned Federated Learning	Oct 30, 2023	Federated Learning	—Unverified
A Federated Learning Framework for Stenosis Detection	Oct 30, 2023	Federated Learning	—Unverified
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression	Oct 29, 2023	Federated Learning	—Unverified
Efficient Cluster Selection for Personalized Federated Learning: A Multi-Armed Bandit Approach	Oct 29, 2023	Federated LearningPersonalized Federated Learning	—Unverified
Peer-to-Peer Deep Learning for Beyond-5G IoT	Oct 29, 2023	Deep LearningFederated Learning	—Unverified
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation	Oct 29, 2023	Federated LearningInformation Retrieval	CodeCode Available
Correlation Aware Sparsified Mean Estimation Using Random Projection	Oct 29, 2023	Distributed OptimizationFederated Learning	—Unverified
Rethinking Semi-Supervised Federated Learning: How to co-train fully-labeled and fully-unlabeled client imaging data	Oct 28, 2023	Federated Learningimage-classification	—Unverified
Contextual Stochastic Bilevel Optimization	Oct 27, 2023	Bilevel OptimizationFederated Learning	—Unverified
Mobile Application for Oral Disease Detection using Federated Learning	Oct 27, 2023	Federated Learningobject-detection	—Unverified
Single-shot General Hyper-parameter Optimization for Federated Learning	Oct 27, 2023	Federated Learning	—Unverified
EcoLearn: Optimizing the Carbon Footprint of Federated Learning	Oct 27, 2023	Federated Learning	—Unverified
Federated Learning over Hierarchical Wireless Networks: Training Latency Minimization via Submodel Partitioning	Oct 27, 2023	Federated Learning	—Unverified
Taming Gradient Variance in Federated Learning with Networked Control Variates	Oct 26, 2023	Federated Learning	—Unverified
Secure short-term load forecasting for smart grids with transformer-based federated learning	Oct 26, 2023	Deep LearningFederated Learning	—Unverified
FedPEAT: Convergence of Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Artificial Intelligence Foundation Models with Mobile Edge Computing	Oct 26, 2023	Deep Reinforcement LearningEdge-computing	—Unverified
FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning	Oct 25, 2023	Federated LearningLanguage Modeling	—Unverified
How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink Channels	Oct 25, 2023	Federated LearningPrivacy Preserving	—Unverified
Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels	Oct 25, 2023	Federated Learning	—Unverified
AirFL-Mem: Improving Communication-Learning Trade-Off by Long-Term Memory	Oct 25, 2023	Federated Learning	—Unverified
Personalized Federated X -armed Bandit	Oct 25, 2023	Federated Learning	—Unverified
Accelerating Split Federated Learning over Wireless Communication Networks	Oct 24, 2023	Federated Learning	—Unverified
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering	Oct 24, 2023	Federated LearningLanguage Modeling	—Unverified
Zero-Knowledge Proof-based Verifiable Decentralized Machine Learning in Communication Network: A Comprehensive Survey	Oct 23, 2023	ArticlesFault Detection	—Unverified
Quantum Federated Learning With Quantum Networks	Oct 23, 2023	Federated LearningTransfer Learning	—Unverified
Federated learning compression designed for lightweight communications	Oct 23, 2023	Cloud ComputingFederated Learning	CodeCode Available
Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation	Oct 23, 2023	Cardiac SegmentationData Augmentation	—Unverified
ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease	Oct 23, 2023	Federated LearningPrivacy Preserving	—Unverified
An Efficient Imbalance-Aware Federated Learning Approach for Wearable Healthcare with Autoregressive Ratio Observation	Oct 23, 2023	Edge-computingFederated Learning	—Unverified
Coordinated Replay Sample Selection for Continual Federated Learning	Oct 23, 2023	Continual LearningFederated Learning	—Unverified
FedSplitX: Federated Split Learning for Computationally-Constrained Heterogeneous Clients	Oct 23, 2023	Federated Learning	—Unverified
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms	Oct 23, 2023	Federated Learning	—Unverified
Dynamically Weighted Federated k-Means	Oct 23, 2023	ClusteringFederated Learning	CodeCode Available
B^2SFL: A Bi-level Blockchained Architecture for Secure Federated Learning-based Traffic Prediction	Oct 23, 2023	Federated LearningPrediction	—Unverified
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification	Oct 22, 2023	Brain Computer InterfaceData Poisoning	—Unverified
PPFL: A Personalized Federated Learning Framework for Heterogeneous Population	Oct 22, 2023	Federated LearningPersonalized Federated Learning	—Unverified

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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