Generalising the discriminative restricted Boltzmann machines
conference contribution
posted on 2023-05-23, 14:44authored byCherla, S, Son TranSon Tran, d'Avila Garcez, A, Weyde, T
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.
History
Publication title
Proceedings of the 26th International Conference on Artificial Neural Networks: Artificial Neural Networks and Machine Learning, Part II
Volume
10614
Pagination
111-119
Department/School
School of Information and Communication Technology
Publisher
Springer
Place of publication
Switzerland
Event title
26th International Conference on Artificial Neural Networks: Artificial Neural Networks and Machine Learning