paper

On-line learning in a discrete state space

arXiv:cond-mat/9705257

Abstract

On-line learning of a rule given by an N-dimensional Ising perceptron, is considered for the case when the student is constrained to take values in a discrete state space of size . For L=2 no on-line algorithm can achieve a finite overlap with the teacher in the thermodynamic limit. However, if is on the order of , Hebbian learning does achieve a finite overlap.

7 pages, 1 Figure, Latex, submitted to J.Phys.A

On-line learning in a discrete state space · wovepaper