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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 176–200 of 311 papers

TitleStatusHype
Selective Knowledge Sharing for Personalized Federated Learning Under Capacity Heterogeneity—0
Self-Aware Personalized Federated Learning—0
Semantic Communication in Dynamic Channel Scenarios: Collaborative Optimization of Dual-Pipeline Joint Source-Channel Coding and Personalized Federated Learning—0
Semi-Synchronous Personalized Federated Learning over Mobile Edge Networks—0
Sheaf HyperNetworks for Personalized Federated Learning—0
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision—0
Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation—0
Take Your Pick: Enabling Effective Personalized Federated Learning within Low-dimensional Feature Space—0
Tensor Decomposition based Personalized Federated Learning—0
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation—0
The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning—0
Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation—0
Towards Layer-Wise Personalized Federated Learning: Adaptive Layer Disentanglement via Conflicting Gradients—0
Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training—0
Towards Personalized Federated Learning—0
Towards Personalized Federated Learning via Comprehensive Knowledge Distillation—0
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation—0
TPFL: A Trustworthy Personalized Federated Learning Framework via Subjective Logic—0
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune—0
UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach—0
Viewport Prediction, Bitrate Selection, and Beamforming Design for THz-Enabled 360° Video Streaming—0
Visual Prompt Based Personalized Federated Learning—0
WAFFLE: Weighted Averaging for Personalized Federated Learning—0
WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models—0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
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