Varieties of Helmholtz machine
Varieties of Helmholtz machine
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DOI：
10.1016/s0893-6080(96)00009-3
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发表时间：
1996-11-01
期刊：
影响因子：
7.8
通讯作者：
Hinton, GE
中科院分区：
文献类型：
--
作者：
Dayan, P;Hinton, GE
Helmholtz机器是一种新的无监督学习架构，它使用自上而下的连接来构建输入的概率密度模型，并使用自下而上的连接来构建与这些模型相反的模型。机器的唤醒-睡眠学习算法只涉及纯粹的局部增量规则。本文提出了几种不同的Helmholtz机器，每一种都有自己的优点和缺点。并将它们与大脑皮层信息处理联系起来。版权所有(C)1996爱思唯尔科学有限公司。
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 (C) 1996 Elsevier Science Ltd.