Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, PMLR 15:233-241, 2011.
Abstract
We introduce the spike and slab Restricted Boltzmann Machine, characterized by having both a real-valued vector, the slab, and a binary variable, the spike, associated with each unit in the hidden layer. The model possesses some practical properties such as being amenable to Block Gibbs sampling as well as being capable of generating similar latent representations of the data to the recently introduced mean and covariance Restricted Boltzmann Machine. We illustrate how the spike and slab Restricted Boltzmann Machine achieves competitive performance on the CIFAR-10 object recognition task. [pdf]
@InProceedings{pmlr-v15-courville11a,
title = {A Spike and Slab Restricted Boltzmann Machine},
author = {Aaron Courville and James Bergstra and Yoshua Bengio},
booktitle = {Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics},
pages = {233--241},
year = {2011},
editor = {Geoffrey Gordon and David Dunson and Miroslav Dudík},
volume = {15},
series = {Proceedings of Machine Learning Research},
address = {Fort Lauderdale, FL, USA},
month = {11--13 Apr},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v15/courville11a/courville11a.pdf},
url = {http://proceedings.mlr.press/v15/courville11a.html},
abstract = {We introduce the spike and slab Restricted Boltzmann Machine, characterized by having both a real-valued vector, the slab, and a binary variable, the spike, associated with each unit in the hidden layer. The model possesses some practical properties such as being amenable to Block Gibbs sampling as well as being capable of generating similar latent representations of the data to the recently introduced mean and covariance Restricted Boltzmann Machine. We illustrate how the spike and slab Restricted Boltzmann Machine achieves competitive performance on the CIFAR-10 object recognition task. [pdf]}
}
%0 Conference Paper
%T A Spike and Slab Restricted Boltzmann Machine
%A Aaron Courville
%A James Bergstra
%A Yoshua Bengio
%B Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics
%C Proceedings of Machine Learning Research
%D 2011
%E Geoffrey Gordon
%E David Dunson
%E Miroslav Dudík
%F pmlr-v15-courville11a
%I PMLR
%J Proceedings of Machine Learning Research
%P 233--241
%U http://proceedings.mlr.press
%V 15
%W PMLR
%X We introduce the spike and slab Restricted Boltzmann Machine, characterized by having both a real-valued vector, the slab, and a binary variable, the spike, associated with each unit in the hidden layer. The model possesses some practical properties such as being amenable to Block Gibbs sampling as well as being capable of generating similar latent representations of the data to the recently introduced mean and covariance Restricted Boltzmann Machine. We illustrate how the spike and slab Restricted Boltzmann Machine achieves competitive performance on the CIFAR-10 object recognition task. [pdf]
TY - CPAPER
TI - A Spike and Slab Restricted Boltzmann Machine
AU - Aaron Courville
AU - James Bergstra
AU - Yoshua Bengio
BT - Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics
PY - 2011/06/14
DA - 2011/06/14
ED - Geoffrey Gordon
ED - David Dunson
ED - Miroslav Dudík
ID - pmlr-v15-courville11a
PB - PMLR
SP - 233
DP - PMLR
EP - 241
L1 - http://proceedings.mlr.press/v15/courville11a/courville11a.pdf
UR - http://proceedings.mlr.press/v15/courville11a.html
AB - We introduce the spike and slab Restricted Boltzmann Machine, characterized by having both a real-valued vector, the slab, and a binary variable, the spike, associated with each unit in the hidden layer. The model possesses some practical properties such as being amenable to Block Gibbs sampling as well as being capable of generating similar latent representations of the data to the recently introduced mean and covariance Restricted Boltzmann Machine. We illustrate how the spike and slab Restricted Boltzmann Machine achieves competitive performance on the CIFAR-10 object recognition task. [pdf]
ER -
Courville, A., Bergstra, J. & Bengio, Y.. (2011). A Spike and Slab Restricted Boltzmann Machine. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, in PMLR 15:233-241
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