On Optimal Early Stopping: Over-informative versus Under-informative Parametrization

Early stopping is a simple and widely used method to prevent over-training neural networks. We develop theoretical results to reveal the relationship between the optimal early stopping time and model dimension as well as sample size of the dataset for certain linear models. Our results demonstrate t...

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Bibliographic Details

Main Authors:	Shen, Ruoqi, Gao, Liyao, Ma, Yi-An
Format:	Journal Article
Language:	English
Published:	20-02-2022
Subjects:	Computer Science - Learning Statistics - Machine Learning
Online Access:	Get full text
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