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 21–30 of 311 papers

Title	Date	Tasks	Status	Hype	Score
Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank Decomposition	Jun 28, 2024	Federated LearningGeneral Knowledge	CodeCode Available	1	5
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training	Jun 1, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
An Empirical Study of Personalized Federated Learning	Jun 27, 2022	BIG-bench Machine LearningFederated Learning	CodeCode Available	1	5
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization	Mar 18, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning	Apr 3, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
FedALA: Adaptive Local Aggregation for Personalized Federated Learning	Dec 2, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated Learning	Dec 16, 2020	Federated LearningIntrusion Detection	CodeCode Available	1	5
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks	Oct 25, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration	Sep 20, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5
Personalized Federated Learning with Adaptive Batchnorm for Healthcare	Dec 1, 2021	Federated LearningPersonalized Federated Learning	CodeCode Available	1	5

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