Automatic Differentiation in MATLAB using ADMAT with Applications (Software, Environments and Tools, Series Number 27) - Softcover

Coleman, Thomas F.; Xu, Wei

Softcover

ISBN 10: 1611974356 ISBN 13: 9781611974355

Publisher: Society for Industrial and Applied Mathematics, 2016

Synopsis

The calculation of partial derivatives is a fundamental need in scientific computing. Automatic differentiation (AD) can be applied straightforwardly to obtain all necessary partial derivatives (usually first and, possibly, second derivatives) regardless of a code s complexity. However, the space and time efficiency of AD can be dramatically improved - sometimes transforming a problem from intractable to highly feasible - if inherent problem structure is used to apply AD in a judicious manner.

Automatic Differentiation in MATLAB using ADMAT with Applications discusses the efficient use of AD to solve real problems, especially multidimensional zero-finding and optimization, in the MATLAB environment. This book is concerned with the determination of the first and second derivatives in the context of solving scientific computing problems with an emphasis on optimization and solutions to nonlinear systems. The authors focus on the application rather than the implementation of AD, solve real nonlinear problems with high performance by exploiting the problem structure in the application of AD, and provide many easy to understand applications, examples, and MATLAB templates.

Audience: This book will prove useful to financial engineers, quantitative analysts, and researchers working with inverse problems, as well as to engineers and applied scientists in other fields.

Contents: Chapter 1: Fundamentals of Automatic Differentiation and the Use of ADMAT; Chapter 2: Products and Sparse Problems; Chapter 3: Using ADMAT with the MATLAB Optimization Toolbox; Chapter 4: Newton's Method and Optimization; Chapter 5: Structure; Chapter 6: Combining C/Fortran with ADMAT; Chapter 7: AD for Inverse Problems with an Application to Computational Finance; Chapter 8: A Template for Structured Problems; Chapter 9: R&D Directions; Appendix A: Installation of ADMAT; Appendix B: How Are Codes Differentiated?

About this title

Book Description

Discussing the efficient use of automatic differentiation to solve real problems in the MATLAB environment, especially multidimensional zero-finding and optimization, this book is concerned with determination of the first and second derivatives in the context of solving scientific computing problems. It will be ideal for financial engineers, quantitative analysts, and researchers.

About the Author

Thomas F. Coleman is Professor, Department of Combinatorics and Optimization and Ophelia Lazaridis University Research Chair, University of Waterloo. He is also the director of WatRISQ, an institute composed of finance researchers that spans several faculties at the university. From 2005 to 2010, Dr. Coleman was Dean of the Faculty of Mathematics, University of Waterloo. Prior to this, he was Professor of Computer Science, Cornell University. He was also the director of the Cornell Theory Center (CTC), a supercomputer applications center, and founded and directed CTC-Manhattan, a computational finance venture. Dr. Coleman has authored three books on computational mathematics, edited six conference proceedings, and published over 80 journal articles in the areas of optimization, automatic differentiation, parallel computing, computational finance, and optimization applications.

Wei Xu is Research Manager at Global Risk Institute (GRI), Toronto. Before joining GRI, Dr. Xu was Visiting Professor at the University of Waterloo. Previously, he was Associate Professor at Tongji University, Shanghai. He cofounded Shanghai Raiyun Information Technology Ltd., a risk management services and solutions provider, and currently serves as its Director of R&D. His research is featured in over 30 publications and he has coauthored a book on risk management.

Edition details

• Publisher: Society for Industrial and Applied Mathematics
• Publication date: 2016
• ISBN 10: 1611974356
• ISBN 13: 9781611974355
• Binding: Paperback
• Language: English
• Number of pages: 117