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Mathematical Optimization for Machine Learning Proceedings of the MATH+ Thematic Einstein Semester 2023

Av: Medverkande: Materialtyp: ArtikelSerie: Utgivningsinformation: Berlin/Boston De Gruyter De Gruyter [Imprint] 2025Beskrivning: 1 electronic resource (202 p.)Innehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783111375854
  • 9783111376776
  • 9783111377742
Ämnen: Onlineresurser: Sammanfattning: 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.
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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.

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