A Combined Quasi-Newton-Type Method Using 4th-Order Directional Derivatives for Solving Degenerate Problems of Unconstrained Optimization

Introduction. Methods of unconstrained optimization play a significant role in machine learning [1–6]. When solving practical problems in machine learning, such as tuning nonlinear regression models, the extremum point of the chosen optimality criterion is often degenerate, which significantly compl...

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Autore principale:	Viktor Zadachyn
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	V.M. Glushkov Institute of Cybernetics 2024-09-01
Serie:	Кібернетика та комп'ютерні технології
Soggetti:	unconstrained optimization quasi-newton methods degenerate minimum point spectral matrix decomposition machine learning
Accesso online:	http://cctech.org.ua/13-vertikalnoe-menyu-en/609-abstract-24-3-2-arte
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