Cover Image

A survey on Clustered Federated Learning: Taxonomy, Analysis and Applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ali, Michael Ben, El-Rifai, Omar, Megdiche, Imen, Peninou, André, Teste, Olivier
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Comparative Evaluation of Clustered Federated Learning Methods
by: Ali, Michael Ben, et al.
Published: (2024)

A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew
by: Ali, Michael Ben, et al.
Published: (2025)

Anomaly detection by partitioning of multi-variate time series
by: Lotte, Pierre, et al.
Published: (2025)

Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
by: Lotte, Pierre, et al.
Published: (2026)

XStacking: Explanation-Guided Stacked Ensemble Learning
by: Garouani, Moncef, et al.
Published: (2025)

IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting
by: Harkati, Aymane, et al.
Published: (2026)

Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework
by: Felten, Florian, et al.
Published: (2023)

Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights
by: Hatfaludi, Cosmin-Andrei, et al.
Published: (2025)

Dynamic Clustering in Federated Learning
by: Kim, Yeongwoo, et al.
Published: (2020)

Distributionally Robust Clustered Federated Learning: A Case Study in Healthcare
by: Konti, Xenia, et al.
Published: (2024)

BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity
by: Guerra-Manzanares, Alejandro, et al.
Published: (2025)

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication
by: Rachmut, Ben, et al.
Published: (2026)

Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions
by: G., Daniel M. Jimenez, et al.
Published: (2024)

Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering
by: Yang, Yifan, et al.
Published: (2024)

Cluster Specific Representation Learning
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)

Strategic Federated Learning: Application to Smart Meter Data Clustering
by: Mohamad, Hassan, et al.
Published: (2024)

Optimizing Communication and Device Clustering for Clustered Federated Learning with Differential Privacy
by: Wei, Dongyu, et al.
Published: (2025)

Clustered Federated Learning via Embedding Distributions
by: Zhang, Dekai, et al.
Published: (2025)

A Taxonomy of Recurrent Learning Rules
by: Martín-Sánchez, Guillermo, et al.
Published: (2022)

FedCCL: Federated Clustered Continual Learning Framework for Privacy-focused Energy Forecasting
by: Helcig, Michael A., et al.
Published: (2025)

Deep Learning For Time Series Analysis With Application On Human Motion
by: Ismail-Fawaz, Ali
Published: (2025)

Distilling A Universal Expert from Clustered Federated Learning
by: Leng, Zeqi, et al.
Published: (2025)

DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning
by: Bekdache, Omar, et al.
Published: (2025)

Single-Round Clustered Federated Learning via Data Collaboration Analysis for Non-IID Data
by: Sugawara, Sota, et al.
Published: (2026)

Fed-BAC: Federated Bandit-Guided Additive Clustering in Hierarchical Federated Learning
by: Bashir, Satwat, et al.
Published: (2026)

Interaction-Aware Gaussian Weighting for Clustered Federated Learning
by: Licciardi, Alessandro, et al.
Published: (2025)

One-Shot Clustering for Federated Learning
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)

Personalized Federated Learning Techniques: Empirical Analysis
by: Khan, Azal Ahmad, et al.
Published: (2024)

Analysis of Total Variation Minimization for Clustered Federated Learning
by: Jung, A.
Published: (2024)

FMCL: Class-Aware Client Clustering with Foundation Model Representations for Heterogeneous Federated Learning
by: Ali, Mahad, et al.
Published: (2026)

Ranking Vectors Clustering: Theory and Applications
by: Fattahi, Ali, et al.
Published: (2025)

Dynamic Clustering for Personalized Federated Learning on Heterogeneous Edge Devices
by: Liu, Heting, et al.
Published: (2025)

Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies
by: Guo, Yongxin, et al.
Published: (2023)

One-Shot Clustering for Federated Learning Under Clustering-Agnostic Assumption
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)

FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling
by: Chen, Cheng, et al.
Published: (2020)

Fairness Regularization in Federated Learning
by: Kharaghani, Zahra, et al.
Published: (2025)

CCFC: Bridging Federated Clustering and Contrastive Learning
by: Liu, Jing, et al.
Published: (2024)

Jigsaw Game: Federated Clustering
by: Xu, Jinxuan, et al.
Published: (2024)

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

Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
by: Raza, Ali, et al.
Published: (2022)