Federated Clustering

Federated clustering addresses the challenge of performing cluster analysis on decentralized datasets without directly sharing sensitive data, a crucial aspect of privacy-preserving machine learning. Current research focuses on developing algorithms like federated k-means and its variants, ensemble methods, and approaches leveraging contrastive learning and generative adversarial networks (GANs) to improve robustness and accuracy in non-independent and identically distributed (non-IID) data settings. This field is significant because it enables collaborative data analysis across multiple institutions or devices while maintaining data privacy, with applications ranging from healthcare to personalized recommendations. The development of efficient and privacy-preserving federated clustering algorithms is a key area of ongoing research.

Papers

November 6, 2024

Fed-EC: Bandwidth-Efficient Clustering-Based Federated Learning For Autonomous Visual Robot Navigation
Shreya Gummadi, Mateus V. Gasparino, Deepak Vasisht, Girish Chowdhary
Autonomous Robot Real Robot Autonomous Robot Navigation Local Learning Dynamic Bandwidth Federated Clustering

September 14, 2024

Distributed Clustering based on Distributional Kernel
Hang Zhang, Yang Xu, Lei Gong, Ye Zhu, Kai Ming Ting
Distributional Learning Federated Clustering Clustering Framework

September 12, 2024

Federated One-Shot Ensemble Clustering
Rui Duan, Xin Xiong, Jueyi Liu, Katherine P. Liao, Tianxi Cai
Federated Prompt Cooperation Cluster Structure Cluster Analysis Federated Clustering Ensemble Clustering Patient Level Multiple Clustering

August 20, 2024

Federated Clustering: An Unsupervised Cluster-Wise Training for Decentralized Data Distributions
Mirko Nardi, Lorenzo Valerio, Andrea Passarella
Decentralized Data Decentralized Machine Learning Federated Clustering Unsupervised Federated Learning

July 17, 2024

Jigsaw Game: Federated Clustering
Jinxuan Xu, Hong-You Chen, Wei-Lun Chao, Yuqian Zhang
K Mean Deep Clustering Jigsaw Puzzle Federated Clustering Unsupervised Feature Learning

February 20, 2024

CCFC++: Enhancing Federated Clustering through Feature Decorrelation
Jie Yan, Jing Liu, Yi-Zi Ning, Zhong-Yuan Zhang
Contrastive Learning Data Heterogeneity Heterogeneous Data Feature Decorrelation Federated Clustering

January 12, 2024

CCFC: Bridging Federated Clustering and Contrastive Learning
Jie Yan, Jing Liu, Zhong-Yuan Zhang
Contrastive Learning Clustering Friendly Representation Federated Clustering Clustering Performance

December 14, 2023

A Framework for Exploring Federated Community Detection
William Leeney, Ryan McConville
New Framework Graph Drawing Graph Structured Data Community Detection Unsupervised Discovery Federated Clustering

October 23, 2023

Dynamically Weighted Federated k-Means
Patrick Holzer, Tania Jacob, Shubham Kavane
Federated Clustering Global Clustering

October 2, 2023

Federated K-means Clustering
Swier Garst, Marcel Reinders
K Mean Different Cluster Separable Data Federated Clustering

September 7, 2023

Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory
Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota
Clustering Algorithm Federated Clustering Clustering Performance Adaptive Resonance

July 25, 2023

Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization
Vassilios Yfantis, Achim Wagner, Martin Ruskowski
Optimization Purpose Distributed Optimization Dual System Large Scale Learning Federated Clustering Dual Formulation Dual Ascent

November 30, 2022

Privacy-Preserving Federated Deep Clustering based on GAN
Jie Yan, Jing Liu, Ji Qi, Zhong-Yuan Zhang
Generative Adversarial Network Deep Clustering Federated Clustering

November 8, 2022

Clustered Federated Learning based on Nonconvex Pairwise Fusion
Xue Yu, Ziyi Liu, Wu Wang, Yifan Sun
Convergence Guarantee Pairwise Learning Federated Clustering Clustered Federated Learning

October 29, 2022

Federated clustering with GAN-based data synthesis
Jie Yan, Jing Liu, Ji Qi, Zhong-Yuan Zhang
Federated Prompt Cooperation Federated Clustering Global Similarity Clustering Framework

October 28, 2022

Machine Unlearning of Federated Clusters
Chao Pan, Jin Sima, Saurav Prakash, Vishal Rana, Olgica Milenkovic
Machine Unlearning Unlearning Framework Federated Clustering

October 20, 2022

An Improved Algorithm for Clustered Federated Learning
Harshvardhan, Avishek Ghosh, Arya Mazumdar
Improved Algorithm Federated Clustering Clustered Federated Learning Clustering Framework Simultaneous Training

August 31, 2022

Federated Online Clustering of Bandits
Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C. S. Lui
Differential Privacy Contextual Multi Armed Bandit Online Clustering Federated Clustering Cooperative Bandit

April 23, 2022

Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets
Federico Lucchetti, Jérémie Decouchant, Maria Fernandes, Lydia Y. Chen, Marcus Völp
Data Set Borda Counting Federated Clustering DNA Sequence Classification

January 18, 2022

Towards Federated Clustering: A Federated Fuzzy $c$-Means Algorithm (FFCM)
Morris Stallmann, Anna Wilbik
Data Clustering Federated Clustering Fuzzy C Mean