Neural networks
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Neural networks
Current advances in Neural networks modeling like neural networks, RBM, boltzmann machines, MCMC, morkov chain, belief networks etc.
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Training Restricted Boltzmann Machines on Word Observations

Training Restricted Boltzmann Machines on Word Observations | Neural networks | Scoop.it

"The restricted Boltzmann machine (RBM) is a flexible tool for modeling complex data, however there have been significant computational difficulties in using RBMs to model high-dimensional multinomial observations. In natural language processing applications, words are naturally modeled by K-ary discrete distributions, where K is determined by the vocabulary size and can easily be in the hundreds of thousands. The conventional approach to training RBMs on word observations is limited because it requires sampling the states of K-way softmax visible units during block Gibbs updates, an operation that takes time linear in K. In this work, we address this issue by employing a more general class of Markov chain Monte Carlo operators on the visible units, yielding updates with computational complexity independent of K. We demonstrate the success of our approach by training RBMs on hundreds of millions of word n-grams using larger vocabularies than previously feasible and using the learned features to improve performance on chunking and sentiment classification tasks, achieving state-of-the-art results on the latter."


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What are advantages of Artificial Neural Networks over Support ...

ANN (Artificial Neural Networks) and SVM (Support Vector Machines) are two popular strategies for supervised machine learning and classification. It's not often clear which method is better for a particular project, and I'm ...
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Deep Neural Networks and Restricted Boltzmann Machines ...

Class diagram for Deep Neural Networks in the Accord.Neuro namespace. Deep neural networks have been listed as a recent breakthrough in signal and image processing applications, such as in speech recognition and ...
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Neural Networks and the Backpropagation Algorithm | Math ...

Neural Networks and the Backpropagation Algorithm | Math ... | Neural networks | Scoop.it
Neurons, as an Extension of the Perceptron Model In a previous post in this series we investigated the Perceptron model for determining whether some data was linearly separable. That is, given a data set where the points ...
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Deep Learning of Representations

Google Tech Talk 11/13/2012 Presented by Yoshua Bengio ABSTRACT Yoshua Bengio will give an introduction to the area of Deep Learning, to which he has been one of the leading contributors.
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The Next Generation of Neural Networks

Google Tech Talks November, 29 2007 In the 1980's, new learning algorithms for neural networks promised to solve difficult classification tasks, like speech ...
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