Abstract
We present a novel theoretical result that generalises the Discriminative Restricted Boltzmann Machine (DRBM). While originally the DRBM was defined assuming the {0, 1}-Bernoulli distribution in each of its hidden units, this result makes it possible to derive cost functions for variants of the DRBM that utilise other distributions, including some that are often encountered in the literature. This paper shows that this function can be extended to the Binomial and {-1,+1}-Bernoulli hidden units.
Author supplied keywords
Cite
CITATION STYLE
Cherla, S., Tran, S. N., D’Avila Garcez, A., & Weyde, T. (2017). Generalising the discriminative restricted boltzmann machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10614 LNCS, pp. 111–119). Springer Verlag. https://doi.org/10.1007/978-3-319-68612-7_13
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
