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 301–311 of 311 papers

Title	Date	Tasks	Status
Personalized Federated Learning with Multiple Known Clusters	Apr 28, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available
Personalized Federated Learning with Server-Side Information	May 23, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available
Personalized Multi-tier Federated Learning	Jul 19, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning	Sep 24, 2022	Federated LearningMeta-Learning	CodeCode Available
Personalized Federated Learning on Long-Tailed Data via Adversarial Feature Augmentation	Mar 27, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available
UPFL: Unsupervised Personalized Federated Learning towards New Clients	Jul 29, 2023	Federated LearningKnowledge Distillation	CodeCode Available
Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series Data	Dec 13, 2024	Causal DiscoveryFederated Learning	CodeCode Available
FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization	May 29, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data	Jan 17, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
Privacy-preserving patient clustering for personalized federated learning	Jul 17, 2023	ClusteringFederated Learning	CodeCode Available
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising	Apr 2, 2023	DenoisingFederated Learning	CodeCode Available

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