Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods-Reference-Cited by-同舟云学术

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Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods

Published:2021-01-27 Issue:3 Volume:30 Page:519-529
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Fong Youyi¹,Xu Jun²

Affiliation:

1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA;

2. Independent Scholar

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2020.1856119

Reference57 articles.

1. Neural networks and principal component analysis: Learning from examples without local minima

2. GTM: The Generative Topographic Mapping

3. Auto-association by multilayer perceptrons and singular value decomposition

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