Articoli correlati a Large-Scale Convex Optimization: Algorithms & Analyses...

Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators - Rilegato

Ryu, Ernest K.; Yin, Wotao

 
9781009160858: Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators
Rilegato
ISBN 10: 1009160850 ISBN 13: 9781009160858
Casa editrice: Cambridge University Press, 2022

Sinossi

A unified analysis of first-order optimization methods, including parallel-distributed algorithms, using monotone operators.

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Informazioni sugli autori

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.

Wotao Yin is Director of the Decision Intelligence Lab with Alibaba Group (US), Damo Academy, and a former Professor of Mathematics at the University of California, Los Angeles. He received his PhD in operations research from Columbia University in 2006. His numerous accolades include an NSF CAREER Award in 2008, an Alfred P. Sloan Research Fellowship in 2009, a Morningside Gold Medal in 2016, and a Damo Award and Egon Balas Prize in 2021. He invented fast algorithms for sparse optimization, image processing, and large-scale distributed optimization problems, and is among the top 1 percent of cited researchers by Clarivate Analytics. His research interests include computational optimization and its applications in signal processing, machine learning, and other data science problems.

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Editore
Cambridge University Press
Data di pubblicazione
2022
Lingua
Inglese
ISBN 10 
1009160850
ISBN 13 
9781009160858
Rilegatura
Copertina rigida
Numero di pagine
318
Contatto del produttore
Cambridge University Press
https://www.cambridge.org/

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