An Improved Hybrid Model for Nonlinear Regression with Missing Values Using Deep Quasi‐Linear Kernel

Author:

Zhu Huilin1,Hu Jinglu1

Affiliation:

1. Graduate School of Information, Production and Systems Waseda University Hibikino 2‐7, Wakamatsu‐ku Kitakyushu 808‐0135 Japan

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Reference25 articles.

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3. Hua‐YanS Ye‐LiL Yun‐FeiZ XuH.Accelerating EM missing data filling algorithm based on the k‐means.2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) IEEE 2018 pp. 401–406.

4. CostaAF SantosMS SoaresJP AbreuPH.Missing data imputation via denoising autoencoders: the untold story.International Symposium on Intelligent Data Analysis Springer 2018 pp. 87–98.

5. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion;Vincent P;Journal of Machine Learning Research,2010

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1. Authors' Reply to the Comments by Kamata et al.;IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences;2023-11-01

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