Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023 (De Gruyter Proceedings in Mathematics)
Author: Konstantin Fackeldey (Editor), Aswin Kannan (Editor), Sebastian Pokutta (Editor), Kartikey Sharma (Editor), Daniel Walter (Editor), Andrea Walther (Editor), Martin Weiser (Editor)
Publisher finelybook 出版社: De Gruyter
Publication Date 出版日期: 2025-05-06
Edition 版本: 1st
Language 语言: English
Print Length 页数: 212 pages
ISBN-10: 3111375854
ISBN-13: 9783111375854
Book Description
Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete optimization, nonlinear programming, optimal control, first-order methods, multilevel optimization, machine learning in optimization, physics-informed learning, and fairness in machine learning.
About the Author
M. Weiser, S. Pokutta, K. Sharma, ZIB, Germany; K. Fackeldey, TU Berlin; A. Kannan, D. Walter, A. Walther, Humboldt-Univ. Germany.
