| Literature DB >> 12662541 |
Geoffrey E. Hinton1, Peter Dayan.
Abstract
The Helmholtz machine is a new unsupervised learning architecture that uses top-down connections to build probability density models of input and bottom-up connections to build inverses to those models. The wake-sleep learning algorithm for the machine involves just the purely local delta rule. This paper suggests a number of different varieties of Helmholtz machines, each with its own strengths and weaknesses, and relates them to cortical information processing. Copyright 1996 Elsevier Science Ltd.Year: 1996 PMID: 12662541 DOI: 10.1016/s0893-6080(96)00009-3
Source DB: PubMed Journal: Neural Netw ISSN: 0893-6080