A Hybrid Model for Nonlinear Regression with Missing Data Using Quasilinear Kernel
Author:
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
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23253
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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
2. An Improved Hybrid Model for Nonlinear Regression with Missing Values Using Deep Quasi‐Linear Kernel;IEEJ Transactions on Electrical and Electronic Engineering;2022-06-20
3. Establishing A Hybrid Pieceswise Linear Model for Air Quality Prediction Based Missingness Challenges;2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2021-10-17
4. A Winner‐Take‐All Autoencoder Based Pieceswise Linear Model for Nonlinear Regression with Missing Data;IEEJ Transactions on Electrical and Electronic Engineering;2021-08-05
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