SOTAVerified

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

Showing 59516000 of 6771 papers

TitleStatusHype
Continual Distributed Learning for Crisis Management0
Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression0
A Graph Federated Architecture with Privacy Preserving Learning0
Communication-Efficient and Personalized Federated Lottery Ticket Learning0
FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia0
FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework0
Wireless Federated Learning (WFL) for 6G Networks -- Part II: The Compute-then-Transmit NOMA Paradigm0
Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends0
Robust Federated Learning by Mixture of ExpertsCode0
Blockchain based Privacy-Preserved Federated Learning for Medical Images: A Case Study of COVID-19 CT Scans0
Gradient Masked Federated Optimization0
A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things0
Turning Federated Learning Systems Into Covert Channels0
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation0
Research on Resource Allocation for Efficient Federated Learning0
Federated Word2Vec: Leveraging Federated Learning to Encourage Collaborative Representation Learning0
Federated Learning of User Verification Models Without Sharing Embeddings0
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing TasksCode0
FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning0
Federated Learning for Internet of Things: A Comprehensive Survey0
On the Importance of Trust in Next-Generation Networked CPS Systems: An AI Perspective0
CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework0
See through Gradients: Image Batch Recovery via GradInversion0
D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning0
Personalized Semi-Supervised Federated Learning for Human Activity Recognition0
Efficient Ring-topology Decentralized Federated Learning with Deep Generative Models for Industrial Artificial Intelligent0
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems0
Decentralized Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities0
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter ItCode0
BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated LearningCode0
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector0
Federated Generalized Face Presentation Attack Detection0
Towards Causal Federated Learning For Enhanced Robustness and Privacy0
Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges0
Federated Learning-based Active Authentication on Mobile Devices0
Sample-based and Feature-based Federated Learning for Unconstrained and Constrained Nonconvex Optimization via Mini-batch SSCACode0
FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search0
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks0
Joint Optimization of Communications and Federated Learning Over the Air0
Empowering Prosumer Communities in Smart Grid with Wireless Communications and Federated Edge Learning0
On-device Federated Learning with Flower0
FedFace: Collaborative Learning of Face Recognition Model0
Communication-Efficient Agnostic Federated Averaging0
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization0
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges0
FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic0
A Federated Learning Framework for Non-Intrusive Load Monitoring0
Knowledge Distillation For Wireless Edge LearningCode0
Fast-adapting and Privacy-preserving Federated Recommender System0
Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SiloBN + ASAMmIoU49.75Unverified
2SiloBN + SAMmIoU49.1Unverified
3SiloBNmIoU45.96Unverified
4FedSAM + SWAmIoU43.42Unverified
5FedASAM + SWAmIoU43.02Unverified
6FedAvg + SWAmIoU42.48Unverified
7FedASAMmIoU42.27Unverified
8FedSAMmIoU41.22Unverified
9FedAvgmIoU38.65Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAAcc@1-1262Clients68.32Unverified
2FedSAM + SWAAcc@1-1262Clients68.12Unverified
3FedAvg + SWAAcc@1-1262Clients67.52Unverified
4FedASAMAcc@1-1262Clients64.23Unverified
5FedSAMAcc@1-1262Clients63.72Unverified
6FedAvgAcc@1-1262Clients61.91Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients42.64Unverified
2FedASAMACC@1-100Clients39.76Unverified
3FedSAM + SWAACC@1-100Clients39.51Unverified
4FedSAMACC@1-100Clients36.93Unverified
5FedAvgACC@1-100Clients36.74Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients41.62Unverified
2FedASAMACC@1-100Clients40.81Unverified
3FedSAM + SWAACC@1-100Clients39.24Unverified
4FedAvgACC@1-100Clients38.59Unverified
5FedSAMACC@1-100Clients38.56Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients48.72Unverified
2FedSAM + SWAACC@1-100Clients46.76Unverified
3FedASAMACC@1-100Clients46.58Unverified
4FedSAMACC@1-100Clients44.84Unverified
5FedAvgACC@1-100Clients41.27Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients48.27Unverified
2FedASAMACC@1-100Clients47.78Unverified
3FedSAM + SWAACC@1-100Clients46.47Unverified
4FedSAMACC@1-100Clients46.05Unverified
5FedAvgACC@1-100Clients42.17Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients49.17Unverified
2FedSAM + SWAACC@1-100Clients47.96Unverified
3FedASAMACC@1-100Clients45.61Unverified
4FedSAMACC@1-100Clients44.73Unverified
5FedAvgACC@1-100Clients40.43Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAM + SWAACC@1-100Clients42.01Unverified
2FedSAM + SWAACC@1-100Clients39.3Unverified
3FedASAMACC@1-100Clients36.04Unverified
4FedSAMACC@1-100Clients31.04Unverified
5FedAvgACC@1-100Clients30.25Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.97Unverified
2FedASAM + SWAACC@1-100Clients54.79Unverified
3FedSAM + SWAACC@1-100Clients53.67Unverified
4FedSAMACC@1-100Clients53.39Unverified
5FedAvgACC@1-100Clients50.25Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.5Unverified
2FedSAM + SWAACC@1-100Clients54.36Unverified
3FedASAM + SWAACC@1-100Clients54.1Unverified
4FedSAMACC@1-100Clients53.97Unverified
5FedAvgACC@1-100Clients50.66Unverified
#ModelMetricClaimedVerifiedStatus
1FedASAMACC@1-100Clients54.81Unverified
2FedSAMACC@1-100Clients54.01Unverified
3FedSAM + SWAACC@1-100Clients53.9Unverified
4FedASAM + SWAACC@1-100Clients53.86Unverified
5FedAvgACC@1-100Clients49.92Unverified
#ModelMetricClaimedVerifiedStatus
1AdaBestAverage Top-1 Accuracy56.2Unverified