Approximating Continuous Functions on Persistence Diagrams Using Template Functions

The persistence diagram is an increasingly useful tool from Topological Data Analysis, but its use alongside typical machine learning techniques requires mathematical finesse. The most success to date has come from methods that map persistence diagrams into vector spaces, in a way which maximizes th...

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Bibliographic Details
Published in:	Foundations of computational mathematics Vol. 23; no. 4; pp. 1215 - 1272
Main Authors:	Perea, Jose A., Munch, Elizabeth, Khasawneh, Firas A.
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.08.2023 Springer Nature B.V
Subjects:	Algorithms Applications of Mathematics Approximation Cognitive tasks Computer Science Continuity (mathematics) Data analysis Economics Linear and Multilinear Algebras Machine learning Math Applications in Computer Science Mathematical analysis Mathematics Mathematics and Statistics Matrix Theory Numerical Analysis Supervised learning Vector spaces 30L05 Persistent homology 68T05 Featurization Bottleneck distance Machine learning 55N31 Topological data analysis
ISSN:	1615-3375, 1615-3383
Online Access:	Get full text
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