Essential Mathematics for Convex Optimization by Fatma Kilinç-Karzan (Hardback)

£54.99
Available
Product Ref. (e.g. ISBN, SKU)
9781009510523
Published:
26 Jun 2025
Format:
Hardback
Number of pages:
444 pages
Weight:
0.000kgs
This textbook offers a mathematically rigorous introduction to convex optimization, blending classical theory with modern topics. Its elementary treatment based on linear algebra, calculus, and real analysis, focus on mathematical foundations, conversational tone, and over 170 exercises make this one of the most accessible textbooks on the topic.
With an emphasis on timeless essential mathematical background for optimization, this textbook provides a comprehensive and accessible introduction to convex optimization for students in applied mathematics, computer science, and engineering. Authored by two influential researchers, the book covers both convex analysis basics and modern topics such as conic programming, conic representations of convex sets, and cone-constrained convex problems, providing readers with a solid, up-to-date understanding of the field. By excluding modeling and algorithms, the authors are able to discuss the theoretical aspects in greater depth. Over 170 in-depth exercises provide hands-on experience with the theory, while more than 30 'Facts' and their accompanying proofs enhance approachability. Instructors will appreciate the appendices that cover all necessary background and the instructors-only solutions manual provided online. By the end of the book, readers will be well equipped to engage with state-of-the-art developments in optimization and its applications in decision-making and engineering.

About the Author: Fatma Kilinç-Karzan is a Professor of Operations Research at Tepper School of Business, Carnegie Mellon University. She was awarded the 2015 INFORMS Optimization Society Prize for Young Researchers, the 2014 INFORMS JFIG Best Paper Award (with S. Yildiz), and an NSF CAREER Award in 2015. Her research focuses on foundational theory and algorithms for convex optimization and structured nonconvex optimization and their applications in optimization under uncertainty, machine learning, and business analytics. She has been an elected member on the councils of the Mathematical Optimization Society and INFORMS Computing Society, and has served on the editorial boards of MOS-SIAM Book Series on Optimization, MathProgA, MathOR, OPRE, SIAM J Opt, IJOC, and OMS.

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Number of pages 444

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