Questions tagged [restricted-boltzmann-machine]

For questions related to restricted Boltzmann machines, which is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.

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What is the difference between Restricted Boltzmann Machine and Artificial Neural Network?

In the deep learning course I took at the university, the professor touched upon the subject of the Restricted Boltzmann Machine. What I understand from this subject is that this system works ...
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How can I reconstruct sparse one-hot encodings using an RBM?

I am currently working with a categorical-binary RBM, where there are 50 categorical visible units and 25 binary hidden units. The categorical visible units are expressed in one-hot encoding format, ...
1 vote
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104 views

How do I derive the gradient of the log-likelihood of an RBM?

In a Restricted Boltzmann Machine (RBM), the likelihood function is: $$p(\mathbf{v};\mathbf{\theta}) = \frac{1}{Z} \sum_{\mathbf{h}} e^{-E(\mathbf{v},\mathbf{h};\mathbf{\theta})}$$ Where $E$ is the ...
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Purpose of the hidden variables in a Restricted Boltzmann Machine

From the part titled Introducing Latent Variables under subsection 2.2 in this tutorial: Introducing Latent Variables. Suppose we want to model an $m$-dimensional unknown probability distribution $q$ ...
1 vote
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How Restricted Boltzman Machine (RBM) generates hand-written digit?

I am reading RBMs from this paper. In Fig1 they show an example of generating hand-written digit using RBMs. This is the figure they are showing: In the learning step first we sample $h$ from $h \sim ...
1 vote
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Best/quickest approach for tuning the hyperparameters of a restricted boltzmann machine

I have an RBM model which takes extremely long to train and evaluate because of the large number of free parameters and the large amount of input data. What would be the most efficient way of tuning ...
1 vote
0 answers
56 views

How do I sample conditionally from deep belief networks?

Deep belief networks (DBNs) are generative models, where, usually, you sample by thermalising the deepest layer (as it's a restricted Boltzmann machine), and then forward propagating a sample towards ...
1 vote
1 answer
1k views

What is the difference between a stacked restricted Boltzmann machine and deep belief network?

What is the difference between stacked restricted Boltzmann machine (RBM) and deep belief network (DBN)? Are they the same entity? If so, why? Is the latter some specific type of the former? If so, ...
1 vote
0 answers
171 views

What are the differences between a deep belief network, a restricted Boltzmann machine and a deep Boltzmann machine?

Can anyone list the differences between deep Belief network (DBN), restricted Boltzmann machine (RBM), deep Boltzmann machine (DBM) using simple examples? Links to other resources are also ...
2 votes
1 answer
122 views

Does the encoding of a restricted Boltzmann machine improve with more layers?

I'm using a restricted Boltzmann machine (RBM) as an autoencoder. For now, I use a simple architecture of two layers, the input (~100 nodes) and the output (3 nodes) layers. I'm thinking to add more ...
3 votes
0 answers
59 views

How do we calculate the hidden units values in a (restricted) Boltzmann machine?

Now, Boltzmann machines are energy-based undirected networks, meaning there are no forward computations. Instead, for each input configuration $x$, a scalar energy is calculated to asses this ...
6 votes
1 answer
650 views

What is the role of the hidden vectors in restricted Boltzmann machines?

I'm learning about the restricted Boltzmann machine (RBM), and I just came up with two naive understandings of this model. But it seems these two understandings are so different. My first ...