Learning Deep Architectures for AI
by Yoshua Bengio
Publisher: Now Publishers 2009
Number of pages: 130
This monograph discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
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by Zdravko Markov - Central Connecticut State University
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