Fully dynamic clustering and diversity maximization in doubling metrics

DOI10.1007/978-3-031-38906-1_41arXiv2302.07771OpenAlexW4385317103MaRDI QIDQ6139043

Paolo Pellizzoni, Andrea Pietracaprina, Geppino Pucci

Publication date: 16 January 2024

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2302.07771

zbMATH Keywords

outliersdynamic algorithms\(k\)-centerdiversity maximizationcover treematroid center

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Data structures (68P05) Approximation algorithms (68W25)

Cites Work

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• Matroid and knapsack center problems
• Clustering to minimize the maximum intercluster distance
• Efficient Classification for Metric Data
• A Lottery Model for Center-Type Problems With Outliers
• Fully Dynamic k-Center Clustering in Low Dimensional Metrics
• Small Space Stream Summary for Matroid Center
• The Non-Uniform k -Center Problem
• Fully dynamic \(k\)-center clustering with outliers

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