Generative Acoustic-Phonemic-Speaker Model Based on Three-Way Restricted Boltzmann Machine

2016 ◽  
Author(s):  
Toru Nakashika ◽  
Yasuhiro Minami
Keyword(s):  
Restricted Boltzmann Machine ◽  
Boltzmann Machine ◽  
Model Based

The optimization of parallel convolutional RBM based on Spark

2019 ◽  
Vol 17 (02) ◽  
pp. 1940011 ◽  
Author(s):  
Yun Jiang ◽  
Junyu Zhuo ◽  
Juan Zhang ◽  
Xiao Xiao
Keyword(s):  
Deep Learning ◽  
Speech Recognition ◽  
Image Classification ◽  
Image Recognition ◽  
Restricted Boltzmann Machine ◽  
Sequential Algorithm ◽  
Boltzmann Machine ◽  
X Ray ◽  
Model Based ◽  
Traditional Algorithm

With the extensive attention and research of the scholars in deep learning, the convolutional restricted Boltzmann machine (CRBM) model based on restricted Boltzmann machine (RBM) is widely used in image recognition, speech recognition, etc. However, time consuming training still seems to be an unneglectable issue. To solve this problem, this paper mainly uses optimized parallel CRBM based on Spark, and proposes a parallel comparison divergence algorithm based on Spark and uses it to train the CRBM model to improve the training speed. The experiments show that the method is faster than traditional sequential algorithm. We train the CRBM with the method and apply it to breast X-ray image classification. The experiments show that it can improve the precision and the speed of training compared with traditional algorithm.

Robustness Evaluation of Restricted Boltzmann Machine against Memory and Logic Error

2017 ◽  
Vol E100.C (12) ◽  
pp. 1118-1121 ◽  
Author(s):  
Yasushi FUKUDA ◽  
Zule XU ◽  
Takayuki KAWAHARA
Keyword(s):  
Restricted Boltzmann Machine ◽  
Boltzmann Machine
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