Copertina

Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Jiaqi, Chen, Yuzhong, Wu, Yuhang, Das, Mahashweta, Yang, Hao, Ma, Fenglong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Distributed, Parallel, and Cluster Computing Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis
di: Wang, Jiaqi, et al.
Pubblicazione: (2024)

Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
di: Che, Liwei, et al.
Pubblicazione: (2024)

Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
di: Wang, Yujia, et al.
Pubblicazione: (2025)

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning
di: Guo, Shunxin, et al.
Pubblicazione: (2025)

Federated Temporal Graph Clustering
di: Zhou, Zihao, et al.
Pubblicazione: (2024)

TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering
di: Gohari, Rasoul Jafari, et al.
Pubblicazione: (2024)

PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark
di: Zhang, Jianqing, et al.
Pubblicazione: (2023)

DA-PFL: Dynamic Affinity Aggregation for Personalized Federated Learning
di: Yang, Xu, et al.
Pubblicazione: (2024)

FedRIR: Rethinking Information Representation in Federated Learning
di: Huang, Yongqiang, et al.
Pubblicazione: (2025)

A Bayesian Framework for Clustered Federated Learning
di: Wu, Peng, et al.
Pubblicazione: (2024)

GENE-FL: Gene-Driven Parameter-Efficient Dynamic Federated Learning
di: Guo, Shunxin, et al.
Pubblicazione: (2025)

Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting
di: Li, Yi, et al.
Pubblicazione: (2026)

DynLP: Parallel Dynamic Batch Update for Label Propagation in Semi-Supervised Learning
di: Shovan, S M, et al.
Pubblicazione: (2026)

Asynchronous Federated Clustering with Unknown Number of Clusters
di: Zhang, Yunfan, et al.
Pubblicazione: (2024)

Hypernetworks for Model-Heterogeneous Personalized Federated Learning
di: Zhang, Chen, et al.
Pubblicazione: (2025)

Federated Learning based on Pruning and Recovery
di: Ma, Chengjie
Pubblicazione: (2024)

Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
di: Wang, Jiaqi, et al.
Pubblicazione: (2024)

Flexible Clustered Federated Learning for Client-Level Data Distribution Shift
di: Duan, Moming, et al.
Pubblicazione: (2021)

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
di: Li, Yichen, et al.
Pubblicazione: (2024)

DPMM-CFL: Clustered Federated Learning via Dirichlet Process Mixture Model Nonparametric Clustering
di: Jaramillo-Civill, Mariona, et al.
Pubblicazione: (2025)

Federated Graph Learning with Graphless Clients
di: Fu, Xingbo, et al.
Pubblicazione: (2024)

MAP: Model Aggregation and Personalization in Federated Learning with Incomplete Classes
di: Li, Xin-Chun, et al.
Pubblicazione: (2024)

Analytic Personalized Federated Meta-Learning
di: Gu, Shunxian, et al.
Pubblicazione: (2025)

SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning
di: Li, Nan, et al.
Pubblicazione: (2025)

Asynchronous Personalized Federated Learning through Global Memorization
di: Wan, Fan, et al.
Pubblicazione: (2025)

HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning
di: Guo, Zhuoning, et al.
Pubblicazione: (2024)

Communication-Efficient Personalized Federal Graph Learning via Low-Rank Decomposition
di: Liu, Ruyue, et al.
Pubblicazione: (2024)

The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning
di: Wu, Xinghao, et al.
Pubblicazione: (2024)

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks
di: Ambekar, Siddharth, et al.
Pubblicazione: (2024)

Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
di: Yan, Xueming, et al.
Pubblicazione: (2024)

Scheduling for On-Board Federated Learning with Satellite Clusters
di: Razmi, Nasrin, et al.
Pubblicazione: (2024)

CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
di: Zhang, Yu, et al.
Pubblicazione: (2021)

Timely Parameter Updating in Over-the-Air Federated Learning
di: Zhu, Jiaqi, et al.
Pubblicazione: (2025)

Personalized Federated Learning via ADMM with Moreau Envelope
di: Zhu, Shengkun, et al.
Pubblicazione: (2023)

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
di: Yi, Liping, et al.
Pubblicazione: (2023)

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models
di: Yuan, Tianjun, et al.
Pubblicazione: (2025)

DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations
di: Zhu, Guogang, et al.
Pubblicazione: (2024)

Blockchain-based Framework for Scalable and Incentivized Federated Learning
di: Wu, Bijun, et al.
Pubblicazione: (2025)

Personalized Federated Heat-Kernel Enhanced Multi-View Clustering via Advanced Tensor Decomposition Techniques
di: Sinaga, Kristina P.
Pubblicazione: (2025)

Knowledge-Driven Federated Graph Learning on Model Heterogeneity
di: Wu, Zhengyu, et al.
Pubblicazione: (2025)