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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 71–80 of 311 papers

Title	Date	Tasks	Status	Score
Adaptive Expert Models for Personalization in Federated Learning	Jun 15, 2022	Federated LearningMixture-of-Experts	CodeCode Available	5
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning	Jun 9, 2021	Continual LearningFederated Learning	CodeCode Available	5
Fusion of Global and Local Knowledge for Personalized Federated Learning	Feb 21, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available	5
Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Scheme	Apr 24, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	5
FHBench: Towards Efficient and Personalized Federated Learning for Multimodal Healthcare	Apr 15, 2025	BenchmarkingDiagnostic	CodeCode Available	5
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism	Sep 1, 2024	Bayesian OptimizationEvent Detection	CodeCode Available	5
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing	Nov 28, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	5
Learn What You Need in Personalized Federated Learning	Jan 16, 2024	Federated Learningimage-classification	CodeCode Available	5
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning	Dec 21, 2023	Domain GeneralizationFederated Learning	CodeCode Available	5
FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients	Nov 4, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	5

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