The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions
type: Item
instance of: scholarly article
publication date: 2014-09-01T00:00:00Z
PubMed publication ID: 26352238
issue: 9
published in: IEEE Transactions on Pattern Analysis and Machine Intelligence
published in: IEEE Transactions on Software Engineering
DOI: 10.1109/TPAMI.2013.238
volume: 36
title: The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions
page(s): 1874-1887
author: Yoshua Bengio
author: Aaron C. Courville
author: James Bergstra
author: Guillaume Desjardins
language of work or name: English
cites work: Training products of experts by minimizing contrastive divergence
cites work: Tiled convolutional neural networks
cites work: Learning in Markov Random Fields using Tempered Transitions
cites work: Selecting Receptive Fields in Deep Networks
cites work: Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
cites work: Learning Horizontal Connections in a Sparse Coding Model of Natural Images
cites work: Learning Sparse Topographic Representations with Products of Student-t Distributions
cites work: Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning
author name string: Aaron Courville
work available at URL: http://xplorestaging.ieee.org/ielx7/34/6868318/06678502.pdf
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