Loss landscapes and optimization in over-parameterized non-linear systems and neural networks

The success of deep learning is due, to a large extent, to the remarkable effectiveness of gradient-based optimization methods applied to large neural networks. The purpose of this work is to propose a modern view and a general mathematical framework for loss landscapes and efficient optimization in...

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Bibliographic Details

Published in:	Applied and computational harmonic analysis Vol. 59; pp. 85 - 116
Main Authors:	Liu, Chaoyue, Zhu, Libin, Belkin, Mikhail
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.07.2022
Subjects:	Deep learning Non-linear optimization Over-parameterized models PL⁎ condition Deep learning PL⁎ condition Over-parameterized models Non-linear optimization
ISSN:	1063-5203
Online Access:	Get full text
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