Mathematical Optimization for Machine Learning
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Mathematical optimization
Product details
- ISBN 9783111375854
- Weight: 485g
- Dimensions: 170 x 240mm
- Publication Date: 06 May 2025
- Publisher: De Gruyter
- Publication City/Country: DE
- Product Form: Hardback
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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.
M. Weiser, S. Pokutta, K. Sharma, ZIB, Germany; K. Fackeldey, TU Berlin; A. Kannan, D. Walter, A. Walther, Humboldt-Univ. Germany.
