Deep, Narrow Sigmoid Belief Networks Are Universal Approximators
نویسندگان
چکیده
منابع مشابه
Deep, Narrow Sigmoid Belief Networks Are Universal Approximators
In this note, we show that exponentially deep belief networks can approximate any distribution over binary vectors to arbitrary accuracy, even when the width of each layer is limited to the dimensionality of the data. We further show that such networks can be greedily learned in an easy yet impractical way.
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2008
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2008.12-07-661