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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Bibliographic Details

Published in:	European journal of applied mathematics Vol. 34; no. 4; pp. 738 - 757
Main Authors:	Kreusser, L. M., Osher, S. J., Wang, B.
Format:	Journal Article
Language:	English
Published:	United States Cambridge University Press 01.08.2023
Subjects:	Mathematics
ISSN:	0956-7925, 1469-4425
Online Access:	Get full text
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