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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 271–280 of 311 papers

Title	Date	Tasks	Status
pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models	Jul 7, 2025	Federated LearningPersonalized Federated Learning	CodeCode Available
Fusion of Global and Local Knowledge for Personalized Federated Learning	Feb 21, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available
Adaptive Expert Models for Personalization in Federated Learning	Jun 15, 2022	Federated LearningMixture-of-Experts	CodeCode Available
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing	Nov 28, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available
Personalized Federated Learning via Stacking	Apr 16, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
FHBench: Towards Efficient and Personalized Federated Learning for Multimodal Healthcare	Apr 15, 2025	BenchmarkingDiagnostic	CodeCode Available
FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update	Mar 18, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
Regularizing and Aggregating Clients with Class Distribution for Personalized Federated Learning	Jun 12, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
Spectral Co-Distillation for Personalized Federated Learning	Jan 29, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
PeFLL: Personalized Federated Learning by Learning to Learn	Jun 8, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available

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