Moment and polynomial optimization is an active research field. It is used to solve difficult questions in many areas, including global optimization, tensor computation, saddle points, Nash equilibrium, and bilevel programs, and it has many applications.
Moment and Polynomial Optimization synthesizes current research and applications to provide the reader with
Audience
This book is intended for applied mathematicians, engineers, and researchers entering the field. It can be used as a textbook for graduate students in courses on convex optimization, polynomial optimization, and matrix and tensor optimization.
About the Author
Jiawang Nie is a professor of mathematics at the University of California, San Diego. He is a Tucker Prize finalist and a recipient of the NSF Career Award, Hellman Fellowship, Optimization Society Young Researchers Prize, SIAG/LA Prize, and Feng Kang Prize and a Fellow of AMS. His research interests include moment and polynomial optimization, convex algebraic geometry, matrix and tensor computation, and various data science computational problems.
a systematic introduction to theory and methods,
a comprehensive approach for extracting optimizers and solving truncated moment problems, and
a creative methodology for using optimality conditions to construct tight Moment-SOS relaxations.
Published:2023
ISBN:978-1-61197-759-2
eISBN:978-1-61197-760-8
https://doi.org/10.1137/1.9781611977608
Book Series Name:MOS-SIAM Series on Optimization
Book Code:MO31
Book Pages:xvi + 467
