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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 281–290 of 311 papers

Title	Date	Tasks	Status
FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients	Nov 4, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees	Oct 11, 2024	Federated LearningPersonalized Federated Learning	CodeCode Available
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment	May 10, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available
Straggler-Resilient Personalized Federated Learning	Jun 5, 2022	Federated LearningLearning Theory	CodeCode Available
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning	Feb 10, 2022	Federated LearningPersonalized Federated Learning	CodeCode Available
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity	Dec 20, 2023	Federated LearningPersonalized Federated Learning	CodeCode Available
Personalized Federated Learning with Contextual Modulation and Meta-Learning	Dec 23, 2023	Federated LearningMeta-Learning	CodeCode Available
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks	Feb 17, 2022	Data PoisoningFederated Learning	CodeCode Available
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism	Sep 1, 2024	Bayesian OptimizationEvent Detection	CodeCode Available
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques	Feb 19, 2021	Federated LearningPersonalized Federated Learning	CodeCode Available

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