Title :
The high-order Boltzmann machine: learned distribution and topology
Author :
Albizuri, F.X. ; Anjou, A.D. ; Grana, M. ; Torrealdea, J. ; Hernandez, M.C.
Author_Institution :
Dept. of Comput. Sci. & Artificial Intelligence, Univ. of the Basqie Country, Sebastian, Spain
fDate :
5/1/1995 12:00:00 AM
Abstract :
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
Keywords :
Boltzmann machines; convergence; learning (artificial intelligence); pattern recognition; probability; topology; Bahadur-Lazarsfeld expansion; convergence; high-order Boltzmann machine; learning algorithm; neural networks; probability distribution; statistical pattern recognition; stochastic network; topology; Computer science education; Convergence; Educational institutions; Machine learning; Network topology; Neural networks; Pattern recognition; Probability distribution; Stochastic processes; Temperature;
Journal_Title :
Neural Networks, IEEE Transactions on
