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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 201–250 of 311 papers

TitleStatusHype
Take Your Pick: Enabling Effective Personalized Federated Learning within Low-dimensional Feature Space—0
Privacy-preserving patient clustering for personalized federated learningCode0
Advances and Challenges in Meta-Learning: A Technical Review—0
Personalized Federated Learning via Amortized Bayesian Meta-Learning—0
FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning—0
Provably Personalized and Robust Federated LearningCode0
PeFLL: Personalized Federated Learning by Learning to LearnCode0
Personalization Disentanglement for Federated Learning: An explainable perspective—0
Personalized Federated Domain Adaptation for Item-to-Item Recommendation—0
Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity—0
Federated Neural Compression Under Heterogeneous Data—0
pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning—0
Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training—0
A novel parameter decoupling approach of personalized federated learning for image analysis—0
FedDWA: Personalized Federated Learning with Dynamic Weight AdjustmentCode0
Collaborative Chinese Text Recognition with Personalized Federated Learning—0
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM—0
Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization—0
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification—0
IP-FL: Incentivized and Personalized Federated Learning—0
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET DenoisingCode0
Personalized Federated Learning with Local Attention—0
Personalized Federated Learning on Long-Tailed Data via Adversarial Feature AugmentationCode0
Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks—0
Visual Prompt Based Personalized Federated Learning—0
Fusion of Global and Local Knowledge for Personalized Federated LearningCode0
FedABC: Targeting Fair Competition in Personalized Federated Learning—0
Cross-Fusion Rule for Personalized Federated Learning—0
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks—0
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation—0
Convergence of First-Order Algorithms for Meta-Learning with Moreau Envelopes—0
Reliable and Interpretable Personalized Federated Learning—0
How To Prevent the Poor Performance Clients for Personalized Federated Learning?—0
Personalized Semantics Excitation for Federated Image Classification—0
Hierarchical Over-the-Air FedGradNorm—0
Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics—0
PGFed: Personalize Each Client's Global Objective for Federated LearningCode0
Flow: Per-Instance Personalized Federated Learning Through Dynamic RoutingCode0
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning—0
Personalized Federated Learning with Hidden Information on Personalized Prior—0
Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery—0
Personalized Federated Learning with Multi-branch Architecture—0
Federated Learning for Chronic Obstructive Pulmonary Disease Classification with Partial Personalized Attention Mechanism—0
Prototype-Based Layered Federated Cross-Modal Hashing—0
Personalized Federated Learning via Heterogeneous Modular NetworksCode0
Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning—0
Find Your Friends: Personalized Federated Learning with the Right Collaborators—0
Group Personalized Federated Learning—0
PersA-FL: Personalized Asynchronous Federated Learning—0
Semi-Synchronous Personalized Federated Learning over Mobile Edge Networks—0
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