Buch, Englisch, Band 808, 250 Seiten, Book, Format (B × H): 155 mm x 235 mm
Buch, Englisch, Band 808, 250 Seiten, Book, Format (B × H): 155 mm x 235 mm
Reihe: Springer Optimization and Its Applications
ISBN: 978-0-387-92856-2
Verlag: Springer-Verlag New York
There have been dramatic improvements in the algorithms and techniques used in machine learning over the last twenty years. Numerous methods have been developed that utilize mathematical programming techniques that are well known to operations researchers. Because understanding of the fundamentals of mathematical programming is essential for theoretical computer scientists, this book intends to provide this audience a strong introduction to the analysis and mathematical programming techniques used in machine learning. Additionally, the book offers operations researchers various examples of machine learning's applications to optimization and modeling.
Primary Audience for Work: Researchers and practitioners in fields of Computer Science and Operations Research
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik Mathematik Operations Research
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
-Introduction. -Nonlinear Programming Problems. -Combinatorial Optimization. -The theory of NP-completeness. -Classification Models.- Regression Models. -Clustering.
