Mathematical programming in machine learning

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 INDICE: -Introduction. -Nonlinear Programming Problems. -Combinatorial Optimization. -The theory of NP-completeness. -Classification Models.- Regression Models. -Clustering.

• ISBN: 978-0-387-92856-2
• Editorial: Springer
• Encuadernacion: Rústica
• Páginas: 250
• Fecha Publicación: 29/03/2013
• Nº Volúmenes: 1
• Idioma: Inglés