Über den Autor
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.
Inhaltsverzeichnis
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.
