Mathematical Optimization for Machine Learning
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Produktnummer:
9783111375854
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.
| EAN: | 9783111375854 |
|---|---|
| Sprache: | Englisch |
| Seitenzahl: | 202 |
| Produktart: | Gebunden |
| Herausgeber: | Fackeldey, Konstantin Kannan, Aswin Pokutta, Sebastian Sharma, Kartikey Walter, Daniel Walther, Andrea Weiser, Martin |
| Verlag: | De Gruyter |
| Untertitel: | Proceedings of the MATH+ Thematic Einstein Semester 2023 |
| Schlagworte: | Nichtlineare Optimierung |
| Größe: | 170 × 240 |
| Gewicht: | 485 g |
