Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023
Konstantin Fackeldey (editor), Aswin Kannan (editor), Sebastian Pokutta (editor), Kartikey Sharma (editor), Daniel Walter (editor), Andrea Walther (editor), Martin Weiser (editor)
Hardback Published on: 06/05/2025
Price: £145.50
Synopsis
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.
Publisher information
- Publisher: De Gruyter
- ISBN: 9783111375854
- Number of pages: 212
- Dimensions: 240 x 170 mm
- Weight: 485g
- Languages: English