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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
An Optimal Transport Approach to Personalized Federated Learning—0
A Novel Algorithm for Personalized Federated Learning: Knowledge Distillation with Weighted Combination Loss—0
A novel parameter decoupling approach of personalized federated learning for image analysis—0
A Parameter Aggregation Strategy on Personalized Federated Learning—0
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection—0
Asynchronous Personalized Federated Learning through Global Memorization—0
A Theorem of the Alternative for Personalized Federated Learning—0
Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning—0
Bayesian Neural Network For Personalized Federated Learning Parameter Selection—0
Bayesian Personalized Federated Learning with Shared and Personalized Uncertainty Representations—0
CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learning—0
Client-supervised Federated Learning: Towards One-model-for-all Personalization—0
Communication-Efficient Personalized Federated Learning for Speech-to-Text Tasks—0
Contextual Stochastic Bilevel Optimization—0
Convergence of First-Order Algorithms for Meta-Learning with Moreau Envelopes—0
Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning—0
Cross-Fusion Rule for Personalized Federated Learning—0
DA-PFL: Dynamic Affinity Aggregation for Personalized Federated Learning—0
Decentralized Directed Collaboration for Personalized Federated Learning—0
Decentralized Personalized Federated Learning—0
Decentralized Personalized Federated Learning for Min-Max Problems—0
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates—0
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks—0
DP^2-FedSAM: Enhancing Differentially Private Federated Learning Through Personalized Sharpness-Aware Minimization—0
DP2FL: Dual Prompt Personalized Federated Learning in Foundation Models—0
Efficient Cluster Selection for Personalized Federated Learning: A Multi-Armed Bandit Approach—0
Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach—0
Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning—0
Energy-Aware Edge Association for Cluster-based Personalized Federated Learning—0
Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling—0
Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering—0
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning—0
Exploring Personalized Federated Learning Architectures for Violence Detection in Surveillance Videos—0
Factor-Assisted Federated Learning for Personalized Optimization with Heterogeneous Data—0
Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching—0
Fault Detection in Telecom Networks using Bi-level Federated Graph Neural Networks—0
FedABC: Targeting Fair Competition in Personalized Federated Learning—0
Robustness and Personalization in Federated Learning: A Unified Approach via Regularization—0
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data—0
FedASTA: Federated adaptive spatial-temporal attention for traffic flow prediction—0
FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning—0
FedCRL: Personalized Federated Learning with Contrastive Shared Representations for Label Heterogeneity in Non-IID Data—0
FedD2S: Personalized Data-Free Federated Knowledge Distillation—0
Federated Learning for Chronic Obstructive Pulmonary Disease Classification with Partial Personalized Attention Mechanism—0
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification—0
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions—0
Federated Neural Compression Under Heterogeneous Data—0
FedGlu: A personalized federated learning-based glucose forecasting algorithm for improved performance in glycemic excursion regions—0
FedGradNorm: Personalized Federated Gradient-Normalized Multi-Task Learning—0
FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning—0
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