Ernest K. Ryu (Seoul National University), Wotao Yin (Los Angeles University of California)

Large-Scale Convex Optimization

• Gebundenes Buch

Produktbeschreibung

This introduction to the theory of convex optimization algorithms presents a unified analysis of first-order optimization methods using the abstraction of monotone operators. The text empowers graduate students in mathematics, computer science, and engineering to choose and design the splitting methods best suited for a given problem.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 400
• Erscheinungstermin: 1. Dezember 2022
• Englisch
• Abmessung: 260mm x 182mm x 23mm
• Gewicht: 790g
• ISBN-13: 9781009160858
• ISBN-10: 1009160850
• Artikelnr.: 63660608

Autorenporträt

Ernest K. Ryu is Assistant Professor of Mathematical Sciences at Seoul National University. He previously served as Assistant Adjunct Professor with the Department of Mathematics at the University of California, Los Angeles from 2016 to 2019, before joining Seoul National University in 2020. He received a BS with distinction in physics and electrical engineering from the California Institute of Technology in 2010; and then an MS in statistics and a PhD - with the Gene Golub Best Thesis Award - in computational mathematics at Stanford University in 2016. His current research focuses on mathematical optimization and machine learning.

Inhaltsangabe

Preface
1. Introduction and preliminaries
Part I. Monotone Operator Methods: 2. Monotone operators and base splitting schemes
3. Primal-dual splitting methods
4. Parallel computing
5. Randomized coordinate update methods
6. Asynchronous coordinate update methods
Part II. Additional Topics: 7. Stochastic optimization
8. ADMM-type methods
9. Duality in splitting methods
10. Maximality and monotone operator theory
11. Distributed and decentralized optimization
12. Acceleration
13. Scaled relative graphs
Appendices
References
Index.