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11 views

GB-RBM unable to learn and generate simple 2D-Motions?

I am trying to apply a GB-RBM to a variation of the LASA Handwriting Dataset to be able to generate new examples. My dataset contains motion trajectories of simple shapes like 'S' shapes, spirals, 'C' ...
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0answers
24 views

How to implement a Gaussian-Rectified RBM and generate data?

I have a bit trouble implementing a gaussian-rectified RBM. I would like to show you how I would implement it. It would be nice if you point out errors or comment the implementation. These are the ...
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0answers
17 views

Associate different continuous types of data with Restricted Boltzmann Machines

This demo shows the DBNs capability to associate different input modalities ("images of digits" and "labels"). By clamping one modality at the top layer, the network can infer the other via (Gibbs) ...
2
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1answer
94 views

Sparse Autoencoder [Hyper]parameters

I have just started using the autoencoder package in R. http://cran.r-project.org/web/packages/autoencoder/index.html Inputs to the autoencode() function include lambda, beta, rho and epsilon. What ...
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0answers
19 views

Time and space complexity of Deep Belief Nets (DBN)

What is the time and space(memory) complexity of DBNs? given d:number of dimensions(attributes), n:number of records, and l:number of hidden layers.
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0answers
24 views

Is deep belief network a belief network [closed]

I am new to deep learning. Please help me.. What is belief network. What is the use of it? How to learn belief networks? Is deep belief network a belief network with multiple layers?
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1answer
40 views

Summarization of text documents (legal domain) using deep learning techniques

I am referring to the site deeplearning.net on how to implement the deep learning architectures. I have read quite a few research papers on document summarization (both single document and ...
0
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1answer
37 views

definition of deep belief network

I was studying Deep Belief Network (DBN) and have questions. 1) According to the definition of DBN, DBN is formed by stacking RBM on top of each other such that the hidden layer in a lower layer ...
1
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1answer
38 views

Guideline to select the hyperparameters in Deep Learning

I'm looking for a paper that could help in giving a guideline on how to choose the hyperparameters of a deep architecture, like stacked auto-encoders or deep believe networks. There are a lot of ...
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1answer
61 views

Comparing different deep learning models?

Does anyone know a paper that describes the differences and compares the different deep learning architectures? like Stacked autoencoders, deep believe networks, maxout networks ... etc.
5
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1answer
168 views

Deep belief networks or Deep Boltzmann Machines?

I'm kinda confused. Is there a difference between Deep belief networks and Deep Boltzmann Machines? Are they different stuff or same thing?! If so, what's the difference?
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0answers
17 views

Deep belief nets and PCA

I have been using successfully DBNs for classification for MNIST and some other tasks. I was thinking of doing dimensionality reduction before training, in order to boost performance. However, when I ...
0
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0answers
86 views

Is a Gaussian-Gaussian RBM just a linear model?

The 'conventional' configuration of RBMs are Binary-Binary and Gaussian-Binary (and sometimes Binary-Gaussian) units. Although it is possible for both the visible and hidden units to be gaussian, ...
3
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1answer
103 views

Are Restricted Boltzmann Machines better than Stacked Auto encoders and why?

So I'm learning about deep learning. I first learned about stacked auto-encoders and now I'm learning about Restricted Boltzmann Machines. However non in the papers/tutorials I read I found them ...
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0answers
42 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 ...
1
vote
1answer
79 views

Why features compression is good?

I'm reading about deep learning and that in principles it's a features compression technique and that is why it works. Now my question is why compressing features from 200 or so into 4 is better? How ...
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0answers
23 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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0answers
34 views

Can not classify Iris dataset by continuous deep belief network

We have a case to map real input values into low dimensional binary vectors. So we use CDBN here, but whatever I change the parameter combinations of k, lr or epochs, it always failed to classify our ...
3
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1answer
97 views

Can a deep belief network (stacked RBMS) be used solely as a dataset generator?

I have a large dataset (tens of thousands of predictors) on which I would like to perform feature reduction with the intent of better model-building for prediction. Deep Belief Networks seem to ...
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2answers
74 views

How to update weights in RBM (Restricted Boltzmann Machines)?

Related Question: Learning weights in a Boltzmann Machine I'm trying to understand RBMs and how they are applied in training of Deep Architecture. Being new to the field of statistics, I stumbled ...
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1answer
250 views

Where and why does deep learning shine?

With all the media talk and hype about deep learning these days, I read some elementary stuff about it. I just found that it is just another machine learning method to learn patterns from data. But my ...
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3answers
248 views

How true is this slide on deep learning?

I was listening to a talk and saw this slide: How true is it?
2
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1answer
120 views

Deep Belief Network (number of layers)

So we have "several RBMs" Deep Belief Network ...
14
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2answers
3k views

Using deep learning for time series prediction

I'm new in area of deep learning and for me first step was to read interesting articles from deeplearning.net site. In papers about deep learning, Hinton and others mostly talk about applying it to ...
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1answer
118 views

Sampling from a Deep Belief Network: Treatment of biases in directed part of the model

When generating samples from a DBN, how do you handle the biases that have been learned for the layers below? I know that you normally perform a number of Block Gibbs sampling steps in the undirected ...
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1answer
161 views

Mathematically modeling neural networks as graphical models

I am struggling to make the mathematical connection between a neural network and a graphical model. In graphical models the idea is simple: the probability distribution factorizes according to the ...
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2answers
3k views

What is the difference between a neural network and a deep belief network?

I am getting the impression that when people are referring to a 'deep belief' network that this is basically a neural network but very large. Is this correct or does a deep belief network also imply ...
4
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2answers
800 views

Deep belief network performs worse than a simple MLP

I tried to train a deep belief network to recognize digits from the MNIST dataset. Everything works OK, I can train even quite a large network. The problem is that the best DBN is worse than a simple ...
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2answers
213 views

Can deep belief networks be applied to sparse feature vectors/classification problems?

I am trying to beat the performance of an SVM classifier in a text classification task. Input is a bag of words model of sentences with 1 representing presence and 0 representing absence. Output is 1 ...
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3answers
6k views

R libraries for deep learning

I was wondering if there's any good R libraries out there for deep learning neural networks? I know there's the nnet, ...