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.
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.
Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023
212
Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023
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Product Details
| ISBN-13: | 9783111377742 |
|---|---|
| Publisher: | De Gruyter |
| Publication date: | 05/06/2025 |
| Series: | De Gruyter Proceedings in Mathematics |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 212 |
| File size: | 16 MB |
| Note: | This product may take a few minutes to download. |
| Age Range: | 18 Years |