Discriminative feature selection using signed Laplacian restricted Boltzmann machine for speed and generalization improvement of high dimensional data classification-Reference-Cited by-同舟云学术

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Discriminative feature selection using signed Laplacian restricted Boltzmann machine for speed and generalization improvement of high dimensional data classification

Published:2024-03 Issue: Volume:153 Page:111274
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Abroshan Yasser^ORCID,Moattar Mohammad Hossein

Publisher

Elsevier BV

Reference51 articles.

1. Training restricted Boltzmann machines: an introduction;Fischer;Pattern Recognit.,2014

2. Ensemble of jointly trained deep neural network-based acoustic models for reverberant speech recognition;Lee;Digit. Signal Process.,2019

3. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups;Hinton;IEEE Signal Process. Mag.,2012

4. The human splicing code reveals new insights into the genetic determinants of disease;Xiong;Science,2015

5. J. Chung, K. Cho, Y. Bengio, A Character-level Decoder without Explicit Segmentation for Neural Machine Translation, arXiv:1603.06147v4, 2016.

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