A deterministic gradient-based approach to avoid saddle points

Loss functions with a large number of saddle points are one of the major obstacles for training modern machine learning (ML) models efficiently. First-order methods such as gradient descent (GD) are usually the methods of choice for training ML models. However, these methods converge to saddle point...

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Vydané v:	European journal of applied mathematics Ročník 34; číslo 4; s. 738 - 757
Hlavní autori:	Kreusser, L. M., Osher, S. J., Wang, B.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Cambridge University Press 01.08.2023
Predmet:	Mathematics
ISSN:	0956-7925, 1469-4425
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