Finding Meaningful Cluster Structure Amidst Background Noise

DOI10.1007/978-3-319-46379-7_23zbMath1478.68292OpenAlexW2521923684MaRDI QIDQ2831395

Shrinu Kushagra, Shai Ben-David, Samira Samadi

Publication date: 9 November 2016

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

Full work available at URL: https://doi.org/10.1007/978-3-319-46379-7_23

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

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• Data stability in clustering: a closer look
• Center-based clustering under perturbation stability
• A general trimming approach to robust cluster analysis
• Trimmed \(k\)-means: An attempt to robustify quantizers
• On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
• Are Stable Instances Easy?
• Data Stability in Clustering: A Closer Look
• Clustering under Perturbation Resilience

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