Book
Open Access
Mathematical Optimization for Machine Learning
Proceedings of the MATH+ Thematic Einstein Semester 2023
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Edited by:
Konstantin Fackeldey
Language:
English
Published/Copyright:
2025
About this book
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.
- Focuses on the interplay of optimization and machine learning.
- Includes bidirectional relation: ML as optimization and accelerating optimization by ML.
- Provides a broad overview of recent progress in this combination.
Author / Editor information
M. Weiser, S. Pokutta, K. Sharma, ZIB, Germany; K. Fackeldey, TU Berlin; A. Kannan, D. Walter, A. Walther, Humboldt-Univ. Germany.
Topics
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VII |
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Alexandre Caboussat, Maude Girardin and Marco Picasso Open Access Download PDF |
1 |
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Olivier Cots, Rémy Dutto, Sophie Jan and Serge Laporte Open Access Download PDF |
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Rohit Pochampalli and Nicolas R. Gauger Open Access Download PDF |
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Alexander Sikorski, Robert Julian Rabben, Surahit Chewle and Marcus Weber Open Access Download PDF |
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Phillip Semler and Martin Weiser Open Access Download PDF |
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Alexander Heinlein, Amanda A. Howard, Panos Stinis and Damien Beecroft Open Access Download PDF |
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Timo Kreimeier, Andrea Walther and Andreas Griewank Open Access Download PDF |
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Ken Trotti, Samuel A. Cruz Alegría, Rolf Krause and Alena Kopaničáková Open Access Download PDF |
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Pascal Van Hentenryck Open Access Download PDF |
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Max Zimmer, Christoph Spiegel and Sebastian Pokutta Open Access Download PDF |
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Antonio Carlucci, Stefano Grivet-Talocia and Ion Victor Gosea Open Access Download PDF |
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Ganna Shyshkanova, Timo Kreimeier, Lukas Baumgärtner, Franz Bethke and Andrea Walther Open Access Download PDF |
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Philippe L. Toint Open Access Download PDF |
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Publishing information
Pages and Images/Illustrations in book
eBook published on:
May 6, 2025
eBook ISBN:
9783111376776
Hardcover published on:
May 6, 2025
Hardcover ISBN:
9783111375854
Pages and Images/Illustrations in book
Front matter:
10
Main content:
202
Illustrations:
2
Coloured Illustrations:
53
Tables:
27
Keywords for this book
Mathematical optimization; Machine learning; Nonlinear optimization; Discrete optimization; Physics informed learning
Audience(s) for this book
Researchers, practitioners and PhD students, interested in machine learning and mathematical optimization.
Creative Commons
BY-ND 4.0
Safety & product resources
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
