Personalized Federated Learning

The federated learning setup presents numerous challenges including data heterogeneity (differences in data distribution), device heterogeneity (in terms of computation capabilities, network connection, etc.), and communication efficiency. Especially data heterogeneity makes it hard to learn a single shared global model that applies to all clients. To overcome these issues, Personalized Federated Learning (PFL) aims to personalize the global model for each client in the federation.

Papers

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Showing 91–100 of 311 papers

Title	Date	Tasks	Status	Score
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning	Dec 21, 2023	Domain GeneralizationFederated Learning	CodeCode Available	5
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising	Apr 2, 2023	DenoisingFederated Learning	CodeCode Available	5
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing	Nov 28, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	5
FHBench: Towards Efficient and Personalized Federated Learning for Multimodal Healthcare	Apr 15, 2025	BenchmarkingDiagnostic	CodeCode Available	5
Personalizing Federated Instrument Segmentation with Visual Trait Priors in Robotic Surgery	Aug 6, 2024	DisentanglementFederated Learning	CodeCode Available	5
Fusion of Global and Local Knowledge for Personalized Federated Learning	Feb 21, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available	5
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal Transport	Nov 15, 2024	Activity RecognitionFederated Learning	CodeCode Available	5
Personalized Federated Learning via Heterogeneous Modular Networks	Oct 26, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	5
FedAH: Aggregated Head for Personalized Federated Learning	Dec 2, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	5
FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update	Mar 18, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	5

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