SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 311 papers

TitleStatusHype
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
RobWE: Robust Watermark Embedding for Personalized Federated Learning Model Ownership Protection—0
Achieving Personalized Federated Learning with Sparse Local Models—0
A Coalition Formation Game Approach for Personalized Federated Learning—0
ActPerFL: Active Personalized Federated Learning—0
Addressing Data Heterogeneity in Federated Learning with Adaptive Normalization-Free Feature Recalibration—0
Advances and Challenges in Meta-Learning: A Technical Review—0
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond—0
Advancing Personalized Federated Learning: Integrative Approaches with AI for Enhanced Privacy and Customization—0
Agnostic Personalized Federated Learning with Kernel Factorization—0
Show:102550
← PrevPage 8 of 13Next →

No leaderboard results yet.