A Novel Inference of a Restricted Boltzmann Machine

@article{Tanaka2014ANI,
  title={A Novel Inference of a Restricted Boltzmann Machine},
  author={Masayuki Tanaka and Masatoshi Okutomi},
  journal={2014 22nd International Conference on Pattern Recognition},
  year={2014},
  pages={1526-1531}
}
A deep neural network (DNN) pre-trained via stacking restricted Boltzmann machines (RBMs) demonstrates high performance. The binary RBM is usually used to construct the DNN. However, a continuous probability of each node is used as real value state, although the state of the binary RBM's node should be represented by a random binary variable. One of main reasons of this abuse is that it works. One of others is to reduce a computational cost. In this paper, we propose a novel inference of the… CONTINUE READING
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