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Questions tagged [deep-belief-networks]

A type of deep neural network architecture that allows layer-wise unsupervised pre-training.

23 questions with no upvoted or accepted answers
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69 views

State of the Art Status of Deep Boltzmann Machine and Pretraining

I have been reading some old papers by Hinton on deep Boltzmann machine and deep belief networks, but I wonder what the current status is regarding these models: Are DBM and DBN totally outdated? I ...
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37 views

Choosing the number of hidden layers and nodes in a Deep Belief Network

What are the recent advances and current best practices in choosing the number and size of stacked Restricted Boltzmann Machines in Deep Belief Networks ?
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101 views

Do stacked RBM's have any benefits/advantages over CNN?

Do stacked RBM's have any benefits/advantages over CNN? If the concern is about face recognition.
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280 views

What are the most important parameters to tune in a deep belief network?

I am trying to create a Deep Belief Network (DBF) for a binary classification problem. The nolearn package provides a good library for implementing them. I see that there are very many parameters to ...
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125 views

boltzmann machine; from logistic function to boltzmann distribution

I'm trying to understand BM; on this topic, tutorials explain it with two formulas: logistic function for the probabilty of single units $p(unit=1)=\frac{1}{1+e^{-\sum\limits_xwx}}$ and, when the ...
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182 views

Deep Belief Net applied to Netflix Prize?

In Restricted Boltzmann Machines for Collaborative Filtering Restricted Boltzmann Machines (RBMs) are applied to the Netflix Prize data set. An obvious next step might be to use stacks of RBMs (i.e. ...
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330 views

Deep Learning with few features available

I was asked to employ deep learning on some seismic simulation data. Visually, the data is a cube, 1000 x 1000 x 1000. For each point in the cube, there are 3 numeric features [1, 0]. Some of it is ...
2
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1k views

Threshold on tanh or sigmoid in Convolutional neural network

I have read several papers on Convolutional Neural Nets but I am yet to come across any that has used thresholds on tanh or sigmoid to decide whether the neuron will fire or not. Obviously this works ...
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257 views

A paper that proves using the latent features of RBM as input to logistic regression?

I'm looking for a paper that includes a proof that simply training a Restricted Boltzmann Machine and then using the latent features as input to a logistic regression classifier is a correct thing and ...
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275 views

Using deep learning for time series prediction with uncertain time series window size!

I'm new in area of deep learning and I am trying to use deep learning to do prediction on machine generated log data gathered as stream of data. I have seen LSTM an how it can be helpful to train ...
2
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303 views

What are some of the image classification datasets other than MNIST on which Deep Belief Network (DBN) has produced good results?

What are some of the image classification datasets other than MNIST on which Deep Belief Network (DBN) has produced state-of-the-art results? Even if its not state-of-the-art, but, I am looking for ...
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92 views

How to calculate associated degree of freedom of linked nodes in graph

I am working on text analytics and building a knowledge graph with high frequency entities (noun chunks) as graph nodes and their linkage between co-occurrence in a sentence as edges. I am able to ...
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160 views

Is this a really a belief propagation problem?

BACKGROUND This is basically a reputation problem that involves a set of interacting entities $e_i$. Each entity has, in principle, a reputation vector $\vec{b}_i$. That reputation depends on what ...
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205 views

Understanding Deep Belief Networks!

I have implemented Stacked Autoencoder in tensorflow and I was thinking of implementing Deep Belief Networks using Stacked RBM's. I had started reading about DBN's from various websites and through ...
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252 views

Clustering of time series using RBMs/DBN?

I have a sequence of actions dataset. There are 10 different actions, but lets say for simplicity that I have a1 and a2 actions. The data are not stationary. For some time we have one distribution of ...
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294 views

Greedy Training of Deep Belief Networks

I try to understand the justification of Greedy Training for Deep Belief Networks. I read the tutorial at http://deeplearning.net/tutorial/DBN.html and various papers of Hinton,Bengio and other ...
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289 views

How is free energy an unnormalized conditional log-probability?

I am following Bengio's Learning Deep Architectures for AI and at page 28 there is a phrase that confuses me: $a(x)$ is the discriminant function or an unnormalized conditional log-probability, ...
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218 views

What is “Hierarchical Probabilistic Inference” in Honglak Lee's C-DBN?

This question is based on Honglak Lee's paper "Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations". I have implemented a convolutional RBM with ...
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131 views

Rough estimates for training time of deep belief networks

I'm still learning about deep learning. However I'm currently interested to know if deep learning architectures scale well or not. Suppose I have a dataset with 1 million training examples, can you ...
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129 views

Deep Belief Networks: connecting visible bias of higher layers to hidden bias of lower layer?

Suppose we are building a DBN (Deep Belief Network) and we have already trained some lower layers as Restricted Bolzmann Machines. Now we add a new layer, with new weights and new biases for the new ...
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1answer
53 views

Need advice regarding Deep Learning for predictive model

I have been working with neural networks for generation of a predictive model using a multivariate approach. I have come across Deep Learning (or Deep neural networks) as a tool to enhance the success ...
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1answer
27 views

Is there any papers or blogs that discuss the effect of embedding layer dimensionality?

Is there any paper or blog that discuss the effect of the dimensionality of embedding layers? The Embedding layers can be used in deep learning models, like CNN or LSTM.
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1answer
241 views

2 questions about the functions in the `deepnet` Deep Neural Network package in R

I'm using R to perform the Deep Neural Network. But there are so many packages and functions related to neural networks that I am confused. I am wondering about the following two things. What are ...