Approximation algorithm for spherical \(k\)-means problem with penalty

DOI10.3934/jimo.2021067OpenAlexW3156372599MaRDI QIDQ2086912

Yu-Jie Wang, Wei Lv, Chen-Chen Wu, Da-Chuan Xu

Publication date: 26 October 2022

Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/jimo.2021067

zbMATH Keywords

approximation algorithmlocal search algorithm\(k\)-means

Mathematics Subject Classification ID

Combinatorial optimization (90C27) Approximation algorithms (68W25)

Related Items (1)

Approximation Algorithms for Spherical k-Means Problem with Penalties Using Local Search Techniques

Cites Work

• Unnamed Item
• A local search approximation algorithm for \(k\)-means clustering
• Data mining. Concepts and techniques
• NP-hardness of Euclidean sum-of-squares clustering
• The bi-criteria seeding algorithms for two variants of \(k\)-means problem
• The seeding algorithm for \(k\)-means problem with penalties
• The seeding algorithms for spherical \(k\)-means clustering
• An improved approximation algorithm for the \(k\)-means problem with penalties
• Local search approximation algorithms for the \(k\)-means problem with penalties
• Least squares quantization in PCM
• Approximation Schemes for Clustering with Outliers
• Better Guarantees for $k$-Means and Euclidean $k$-Median by Primal-Dual Algorithms
• Spherical k-Means++ Clustering
• The effectiveness of lloyd-type methods for the k-means problem

This page was built for publication: Approximation algorithm for spherical \(k\)-means problem with penalty