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 14011450 of 6771 papers

TitleStatusHype
AugMixCloak: A Defense against Membership Inference Attacks via Image Transformation0
Aggregating Low Rank Adapters in Federated Fine-tuning0
Data Valuation for Vertical Federated Learning: A Model-free and Privacy-preserving Method0
Data value estimation on private gradients0
Data privacy protection in microscopic image analysis for material data mining0
DBFed: Debiasing Federated Learning Framework based on Domain-Independent0
Data Poisoning Attacks on Federated Machine Learning0
Auditable Homomorphic-based Decentralized Collaborative AI with Attribute-based Differential Privacy0
DEAL: Decremental Energy-Aware Learning in a Federated System0
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy0
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning0
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning0
Debiasing Federated Learning with Correlated Client Participation0
Decaf: Data Distribution Decompose Attack against Federated Learning0
Data Overvaluation Attack and Truthful Data Valuation in Federated Learning0
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review0
Decentralised and collaborative machine learning framework for IoT0
Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning0
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement0
Distributed Machine Learning with Sparse Heterogeneous Data0
Decentralised Traffic Incident Detection via Network Lasso0
Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space0
Adaptive Distillation for Decentralized Learning from Heterogeneous Clients0
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo0
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization0
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness0
Decentralized Differentially Private Segmentation with PATE0
Decentralized digital twins of complex dynamical systems0
Decentralized Directed Collaboration for Personalized Federated Learning0
Automated Federated Learning in Mobile Edge Networks -- Fast Adaptation and Convergence0
Decentralized EM to Learn Gaussian Mixtures from Datasets Distributed by Features0
A Graph Federated Architecture with Privacy Preserving Learning0
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach0
Decentralized Federated Domain Generalization with Style Sharing: A Formal Modeling and Convergence Analysis0
Decentralized Federated Learning: A Survey and Perspective0
Decentralized Federated Learning: A Survey on Security and Privacy0
Detection of Global Anomalies on Distributed IoT Edges with Device-to-Device Communication0
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection0
Decentralized federated learning methods for reducing communication cost and energy consumption in UAV networks0
FedNMUT -- Federated Noisy Model Update Tracking Convergence Analysis0
Decentralized federated learning of deep neural networks on non-iid data0
Decentralized Federated Learning on the Edge over Wireless Mesh Networks0
Decentralized Federated Learning Over Imperfect Communication Channels0
Decentralized Federated Learning Preserves Model and Data Privacy0
Decentralized Federated Learning via MIMO Over-the-Air Computation: Consensus Analysis and Performance Optimization0
Decentralized Federated Learning via Mutual Knowledge Transfer0
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks0
Decentralized Federated Learning with Model Caching on Mobile Agents0
Decentralized Federated Reinforcement Learning for User-Centric Dynamic TFDD Control0
Auction Based Clustered Federated Learning in Mobile Edge Computing System0
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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