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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 51–100 of 311 papers

TitleStatusHype
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian RegularizationCode1
Exploiting Shared Representations for Personalized Federated LearningCode1
PFL-MoE: Personalized Federated Learning Based on Mixture of ExpertsCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
Personalized Federated Learning with First Order Model OptimizationCode1
Ditto: Fair and Robust Federated Learning Through PersonalizationCode1
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
Personalized Federated Learning with Moreau EnvelopesCode1
pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language ModelsCode0
Personalized Federated Learning via Dual-Prompt Optimization and Cross Fusion—0
Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning—0
pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization—0
Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling—0
Generalized and Personalized Federated Learning with Foundation Models via Orthogonal Transformations—0
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions—0
Personalized Federated Learning under Model Dissimilarity Constraints—0
Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data—0
Incentivizing Inclusive Contributions in Model Sharing Markets—0
Privacy-Preserving Personalized Federated Learning for Distributed Photovoltaic Disaggregation under Statistical Heterogeneity—0
DP2FL: Dual Prompt Personalized Federated Learning in Foundation Models—0
FHBench: Towards Efficient and Personalized Federated Learning for Multimodal HealthcareCode0
A Novel Algorithm for Personalized Federated Learning: Knowledge Distillation with Weighted Combination Loss—0
Exploring Personalized Federated Learning Architectures for Violence Detection in Surveillance Videos—0
RCC-PFL: Robust Client Clustering under Noisy Labels in Personalized Federated Learning—0
pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning—0
Semantic Communication in Dynamic Channel Scenarios: Collaborative Optimization of Dual-Pipeline Joint Source-Channel Coding and Personalized Federated Learning—0
Mitigating Membership Inference Vulnerability in Personalized Federated Learning—0
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates—0
BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learningCode0
Personalized Federated Learning via Learning Dynamic Graphs—0
WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models—0
Asynchronous Personalized Federated Learning through Global Memorization—0
Personalized Federated Learning for Egocentric Video Gaze Estimation with Comprehensive Parameter Frezzing—0
Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning—0
PFedDST: Personalized Federated Learning with Decentralized Selection Training—0
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data—0
Advancing Personalized Federated Learning: Integrative Approaches with AI for Enhanced Privacy and Customization—0
SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning—0
Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning—0
Integrating Personalized Federated Learning with Control Systems for Enhanced Performance—0
Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning—0
Personalized Federated Learning for Cellular VR: Online Learning and Dynamic Caching—0
pMixFed: Efficient Personalized Federated Learning through Adaptive Layer-Wise Mixup—0
pFedWN: A Personalized Federated Learning Framework for D2D Wireless Networks with Heterogeneous Data—0
Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning—0
Uncertainty-Aware Label Refinement on Hypergraphs for Personalized Federated Facial Expression RecognitionCode0
FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning—0
Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series DataCode0
FedAH: Aggregated Head for Personalized Federated LearningCode0
Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach—0
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