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Data Mining and Mathematical Programming
About this Title
Panos M. Pardalos, University of Florida, Gainesville, FL and Pierre Hansen, HEC Montréal, Montréal, QC, Canada, Editors
Publication: CRM Proceedings and Lecture Notes
Publication Year:
2008; Volume 45
ISBNs: 978-0-8218-4352-9 (print); 978-1-4704-3959-0 (online)
DOI: https://doi.org/10.1090/crmp/045
MathSciNet review: MR2408900
MSC: Primary 62-06; Secondary 68-06, 90-08, 90C09, 90C29
Table of Contents
Front/Back Matter
Chapters
- Support vector machines and distance minimization
- 0-1 semidefinite programming for graph-cut clustering: Modelling and approximation
- Artificial attributes in analyzing biomedical databases
- Recent advances in mathematical programming for classification and cluster analysis
- Nonlinear skeletons of data sets and applications—Methods based on subspace clustering
- Current classification algorithms for biomedical applications
- Bilevel model selection for support vector machines
- Algorithms for detecting complete and partial horizontal gene transfers: Theory and practice
- Nonlinear knowledge in kernel machines
- Ultrametric embedding: Application to data fingerprinting and to fast data clustering
- Selective linear and nonlinear classification