DPMM-CFL: Clustered Federated Learning via Dirichlet Process Mixture Model Nonparametric Clustering
Fuente:
arXiv
Saved in:
| Main Authors: | Jaramillo-Civill, Mariona, Wu, Peng, Closas, Pau |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Bayesian Framework for Clustered Federated Learning
by: Wu, Peng, et al.
Published: (2024)
by: Wu, Peng, et al.
Published: (2024)
SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning
by: Yang, Yuning, et al.
Published: (2024)
by: Yang, Yuning, et al.
Published: (2024)
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
by: Scott, Jonathan, et al.
Published: (2024)
by: Scott, Jonathan, et al.
Published: (2024)
Asynchronous Federated Clustering with Unknown Number of Clusters
by: Zhang, Yunfan, et al.
Published: (2024)
by: Zhang, Yunfan, et al.
Published: (2024)
Scheduling for On-Board Federated Learning with Satellite Clusters
by: Razmi, Nasrin, et al.
Published: (2024)
by: Razmi, Nasrin, et al.
Published: (2024)
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
by: Wang, Jiaqi, et al.
Published: (2024)
by: Wang, Jiaqi, et al.
Published: (2024)
Flexible Clustered Federated Learning for Client-Level Data Distribution Shift
by: Duan, Moming, et al.
Published: (2021)
by: Duan, Moming, et al.
Published: (2021)
Federated K-means Clustering
by: Garst, Swier, et al.
Published: (2023)
by: Garst, Swier, et al.
Published: (2023)
Federated Temporal Graph Clustering
by: Zhou, Zihao, et al.
Published: (2024)
by: Zhou, Zihao, et al.
Published: (2024)
FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure
by: Duan, Moming, et al.
Published: (2020)
by: Duan, Moming, et al.
Published: (2020)
SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning
by: Li, Nan, et al.
Published: (2025)
by: Li, Nan, et al.
Published: (2025)
TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering
by: Gohari, Rasoul Jafari, et al.
Published: (2024)
by: Gohari, Rasoul Jafari, et al.
Published: (2024)
CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
by: Zhang, Yu, et al.
Published: (2021)
by: Zhang, Yu, et al.
Published: (2021)
Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation
by: Tsouvalas, Vasileios, et al.
Published: (2024)
by: Tsouvalas, Vasileios, et al.
Published: (2024)
Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVs
by: Bouchiha, Mouhamed Amine, et al.
Published: (2026)
by: Bouchiha, Mouhamed Amine, et al.
Published: (2026)
A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks
by: Liu, Zhuocheng, et al.
Published: (2025)
by: Liu, Zhuocheng, et al.
Published: (2025)
Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models
by: Campos, Enrique Mármol, et al.
Published: (2024)
by: Campos, Enrique Mármol, et al.
Published: (2024)
Personalized Federated Heat-Kernel Enhanced Multi-View Clustering via Advanced Tensor Decomposition Techniques
by: Sinaga, Kristina P.
Published: (2025)
by: Sinaga, Kristina P.
Published: (2025)
Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
by: Yan, Xueming, et al.
Published: (2024)
by: Yan, Xueming, et al.
Published: (2024)
FedClust: Optimizing Federated Learning on Non-IID Data through Weight-Driven Client Clustering
by: Islam, Md Sirajul, et al.
Published: (2024)
by: Islam, Md Sirajul, et al.
Published: (2024)
Semantic-Aware Scheduling for GPU Clusters with Large Language Models
by: Wang, Zerui, et al.
Published: (2025)
by: Wang, Zerui, et al.
Published: (2025)
FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference
by: Hou, Qijun, et al.
Published: (2026)
by: Hou, Qijun, et al.
Published: (2026)
Revisiting Reliability in Large-Scale Machine Learning Research Clusters
by: Kokolis, Apostolos, et al.
Published: (2024)
by: Kokolis, Apostolos, et al.
Published: (2024)
Aryl: An Elastic Cluster Scheduler for Deep Learning
by: Li, Jiamin, et al.
Published: (2022)
by: Li, Jiamin, et al.
Published: (2022)
Clustered Federated Learning with Hierarchical Knowledge Distillation
by: Ahmad, Sabtain, et al.
Published: (2025)
by: Ahmad, Sabtain, et al.
Published: (2025)
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
by: Li, Zhiqiang, et al.
Published: (2025)
by: Li, Zhiqiang, et al.
Published: (2025)
Federated Hierarchical Clustering with Automatic Selection of Optimal Cluster Numbers
by: Zhang, Yue, et al.
Published: (2026)
by: Zhang, Yue, et al.
Published: (2026)
EncCluster: Scalable Functional Encryption in Federated Learning through Weight Clustering and Probabilistic Filters
by: Tsouvalas, Vasileios, et al.
Published: (2024)
by: Tsouvalas, Vasileios, et al.
Published: (2024)
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
by: Tian, Chunlin, et al.
Published: (2024)
by: Tian, Chunlin, et al.
Published: (2024)
FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation
by: Zhan, Ziwei, et al.
Published: (2024)
by: Zhan, Ziwei, et al.
Published: (2024)
Personalized Federated Learning via ADMM with Moreau Envelope
by: Zhu, Shengkun, et al.
Published: (2023)
by: Zhu, Shengkun, et al.
Published: (2023)
pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2024)
by: Yi, Liping, et al.
Published: (2024)
LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data
by: Zhang, Yuxin, et al.
Published: (2025)
by: Zhang, Yuxin, et al.
Published: (2025)
FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments
by: Pramanik, Anik, et al.
Published: (2026)
by: Pramanik, Anik, et al.
Published: (2026)
Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting
by: Li, Yi, et al.
Published: (2026)
by: Li, Yi, et al.
Published: (2026)
Graph-Regularized Learning of Gaussian Mixture Models
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2025)
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2025)
Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters
by: Luo, Ziyue, et al.
Published: (2025)
by: Luo, Ziyue, et al.
Published: (2025)
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
by: Ma, Mengmeng, et al.
Published: (2024)
by: Ma, Mengmeng, et al.
Published: (2024)
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
by: Wu, Yebo, et al.
Published: (2024)
by: Wu, Yebo, et al.
Published: (2024)
Similar Items
-
A Bayesian Framework for Clustered Federated Learning
by: Wu, Peng, et al.
Published: (2024) -
SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning
by: Yang, Yuning, et al.
Published: (2024) -
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
by: Scott, Jonathan, et al.
Published: (2024) -
Asynchronous Federated Clustering with Unknown Number of Clusters
by: Zhang, Yunfan, et al.
Published: (2024) -
Scheduling for On-Board Federated Learning with Satellite Clusters
by: Razmi, Nasrin, et al.
Published: (2024)