The high-order Boltzmann machine: learned distribution and topology
F.X. Albizuri, Alicia d’Anjou, Manuel Graña, Javier Torrealdea, Carmen Hernández · IEEE Transactions on Neural Networks · 1995
In this paper we give a formal definition of the high-order Boltzmann machine (BM), and extend the well-known results on the convergence of the learning algorithm of the two-order BM. From the Bahadur-Lazarsfeld expansion we characterize the probability distribution learned by the high order BM. Likewise a criterion is given to establish the topology of the BM depending on the significant correlations of the particular probability distribution to be learned.