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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 26–50 of 311 papers

TitleStatusHype
Personalized Federated Learning under Mixture of DistributionsCode1
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization GuaranteesCode1
Tackling Data Heterogeneity in Federated Learning with Class PrototypesCode1
FedALA: Adaptive Local Aggregation for Personalized Federated LearningCode1
FedTP: Federated Learning by Transformer PersonalizationCode1
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural NetworksCode1
Characterizing Internal Evasion Attacks in Federated LearningCode1
FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data DistributionCode1
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI SynthesisCode1
An Empirical Study of Personalized Federated LearningCode1
Personalized Federated Learning via Variational Bayesian InferenceCode1
Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT ImagingCode1
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse TrainingCode1
Efficient Split-Mix Federated Learning for On-Demand and In-Situ CustomizationCode1
SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge IntelligenceCode1
Personalized Federated Learning With GraphCode1
Personalized Federated Learning with Adaptive Batchnorm for HealthcareCode1
Personalized Federated Learning through Local MemorizationCode1
Parameterized Knowledge Transfer for Personalized Federated LearningCode1
Connecting Low-Loss Subspace for Personalized Federated LearningCode1
Federated Multi-Task Learning under a Mixture of DistributionsCode1
On Bridging Generic and Personalized Federated Learning for Image ClassificationCode1
Personalized Federated Learning with Gaussian ProcessesCode1
Personalized Federated Learning by Structured and Unstructured Pruning under Data HeterogeneityCode1
Personalized Federated Learning using HypernetworksCode1
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