A kernel for multi-parameter persistent homology

•We propose the first kernel construction for multi-parameter persistent homology.•Our kernel is generic, stable and can be approximated in polynomial time.•Connect topological data analysis and machine learning for multivariate analysis.•Our technique is applicable to shape analysis, recognition an...

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Vydané v:	Computers & graphics. X Ročník 2; s. 100005
Hlavní autori:	Corbet, René, Fugacci, Ulderico, Kerber, Michael, Landi, Claudia, Wang, Bei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.12.2019
Predmet:	Machine learning Multivariate analysis Persistent homology Topological data analysis Persistent homology Multivariate analysis Topological data analysis Machine learning Persistent Homology Multivariate Analysis Machine Learning Topological Data Analysis
ISSN:	2590-1486, 2590-1486
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