Computational Topology for Data Analysis
Language: English
Published by Cambridge University Press, GB, 2022
- Hardcover
- New
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
AbeBooks seller since June 11, 2025
Condition: New
£ 68.15
Quantity: Over 20 available
Add to basketItem description from seller
Topological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data, and the area has grown substantially both in its methodologies and applicability. Providing a computational and algorithmic foundation for techniques in TDA, this comprehensive, self-contained text introduces students and researchers in mathematics and computer science to the current state of the field. The book features a description of mathematical objects and constructs behind recent advances, the algorithms involved, computational considerations, as well as examples of topological structures or ideas that can be used in applications. It provides a thorough treatment of persistent homology together with various extensions - like zigzag persistence and multiparameter persistence - and their applications to different types of data, like point clouds, triangulations, or graph data. Other important topics covered include discrete Morse theory, the Mapper structure, optimal generating cycles, as well as recent advances in embedding TDA within machine learning frameworks.…
Seller Inventory # LU-9781009098168
- Title
- Computational Topology for Data Analysis
- Author
- Tamal Krishna Dey, Yusu Wang
- Publisher
- Cambridge University Press, GB
- Publication year
- 2022
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1009098160
- ISBN 13
- 9781009098168
- Item weight
- 780 grams
"Synopsis" may belong to another edition of this title.
About the Author
Yusu Wang is Professor in the Halıcıouğlu Data Science Institute at University of California, San Diego. Prior to joining UCSD, she was Professor of Computer Science and Engineering at the Ohio State University and post-doctoral fellow at Stanford University. Yusu primarily works in topological and geometric data analysis, developing effective and theoretically justified algorithms for data analysis using geometric and topological ideas, as well as in applying them to practical domains. She received the DOE Early Career Principal Investigator Award in 2006 and NSF Career Award in 2008.
"About the title" may belong to another edition of this title.
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