Evaluation Complexity of Algorithms for Nonconvex Optimization
Language: English
Published by Society for Industrial and Applied Mathematics,U.S., US, 2022
- Hardcover
- New
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Condition: New
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Add to basketItem description from seller
One of the most popular ways to assess the "effort" needed to solve a problem is to count how many evaluations of the problem functions (and their derivatives) are required. In many cases, this is often the dominating computational cost. Given an optimization problem satisfying reasonable assumptions-and given access to problem-function values and derivatives of various degrees-how many evaluations might be required to approximately solve the problem? Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation, and Perspectives addresses this question for nonconvex optimization problems, those that may have local minimizers and appear most often in practice. This is the first bookon complexity to cover topics such as composite and constrained optimization, derivative-free optimization, subproblem solution, and optimal (lower and sharpness) bounds for nonconvex problems,to address the disadvantages of traditional optimality measures and propose useful surrogates leading to algorithms that compute approximate high-order critical points, and to compare traditional and new methods, highlighting the advantages of the latter from a complexity point of view.This is the go-to book for those interested in solving nonconvex problems. It is suitable for advanced undergraduate and graduate students in courses on Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory.…
Seller Inventory # LU-9781611976984
- Title
- Evaluation Complexity of Algorithms for Nonconvex Optimization
- Author
- Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis
- Publisher
- Society for Industrial and Applied Mathematics,U.S., US
- Publication year
- 2022
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1611976987
- ISBN 13
- 9781611976984
- Item weight
- 1,344 grams
Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation, and Perspectives addresses this question for nonconvex optimization problems, those that may have local minimizers and appear most often in practice. This is the first book
- on complexity to cover topics such as composite and constrained optimization, derivative-free optimization, subproblem solution, and optimal (lower and sharpness) bounds for nonconvex problems,
- to address the disadvantages of traditional optimality measures and propose useful surrogates leading to algorithms that compute approximate high-order critical points, and
- to compare traditional and new methods, highlighting the advantages of the latter from a complexity point of view.
"Synopsis" may belong to another edition of this title.
About the Author
Nicholas I. M. Gould is a Senior Fellow at the STFC-Rutherford Appleton Laboratory in Oxfordshire, and a visiting professor at the Universities of Edinburgh and Oxford. His research interests include the theory and practice of optimization methods, numerical linear algebra, large-scale scientific computation, and the links between these fields.
Philippe L. Toint has been the co-director of the Numerical Analysis Unit and director of the Transportation Research Group at the University of Namur since 1979. His research interests include numerical optimization, numerical analysis, and transportation.
"About the title" may belong to another edition of this title.
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