Mathematical Optimization for Machine Learning
- 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.
| Editor: | Konstantin Fackeldey, Aswin Kannan, Sebastian Pokutta, Kartikey Sharma, Daniel Walter, Andrea Walter, Martin Weiser |
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| Document Type: | Proceedings |
| Series: | De Gruyter Proceedings in Mathematics |
| Publisher: | De Gruyter |
| Year of first publication: | 2025 |
| DOI: | https://doi.org/10.1515/9783111376776 |

