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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 276–300 of 311 papers

TitleStatusHype
Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching—0
Achieving Personalized Federated Learning with Sparse Local Models—0
How to Backdoor HyperNetwork in Personalized Federated Learning?—0
Personalized Federated Learning of Driver Prediction Models for Autonomous Driving—0
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization—0
On-Demand Unlabeled Personalized Federated Learning—0
A Parameter Aggregation Strategy on Personalized Federated Learning—0
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection—0
WAFFLE: Weighted Averaging for Personalized Federated Learning—0
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision—0
Inference-Time Personalized Federated Learning—0
Robust and Personalized Federated Learning with Spurious Features: an Adversarial Approach—0
Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation—0
Agnostic Personalized Federated Learning with Kernel Factorization—0
On Heterogeneously Distributed Data, Sparsity Matters—0
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer—0
Private Multi-Task Learning: Formulation and Applications to Federated LearningCode0
Federated Asymptotics: a model to compare federated learning algorithms—0
Personalized Federated Learning with Clustering: Non-IID Heart Rate Variability Data Application—0
New Metrics to Evaluate the Performance and Fairness of Personalized Federated Learning—0
Sparse Personalized Federated LearningCode0
Personalized Federated Learning over non-IID Data for Indoor Localization—0
UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach—0
Personalized Federated Learning with Contextualized Generalization—0
Decentralized Personalized Federated Learning for Min-Max Problems—0
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