Overview

Moment and polynomial optimization is an active research field 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. The author synthesizes current research and applications, providing 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. 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.

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9781611977592

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Jiawang Nie is a professor of mathematics at the University of California, San Diego. He is a Tucker Prize finalist and recipient of NSF Career Award, Hellman Fellowship, Optimization Society Young Researchers Prize, SIAG/LA Prize, 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.

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