Convolutional Deep Belief Networks / Neural Information Processing Systems / NW NV / Weston / per- Convolutional Deep Belief Networks / Komatsu / /
Continent
America / /
Country
Canada / / /
Event
Product Recall / Product Issues / /
Facility
Stanford University / /
IndustryTerm
hidden / element-wise product / unsupervised learning using graphics processors / energy function / deep belief networks / bottomup processing / energy-based model / sub-network / trivial solutions / deep belief network / energy functions / learning algorithm / learning algorithms / energy / /
Organization
Hierarchical Representations Honglak Lee Roger Grosse Rajesh Ranganath Andrew Y. Ng Computer Science Department / Stanford University / Optical Society / /
Person
Rajat Raina / Andrew Y. Ng / Lee Roger Grosse Rajesh Ranganath Andrew / Daniel Oblinger / Field / /
Position
author / D. J. / hierarchical generative model for full-sized images / General / Sparse deep belief network model for visual area V2 / /
Product
Pentax K-x Digital Camera / curve / /
ProvinceOrState
California / /
PublishedMedium
Journal of the Optical Society of America A / Machine Learning / /
SportsLeague
Stanford University / /
Technology
deep unsupervised learning using graphics processors / neural network / artificial intelligence / Machine Learning / /
Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations Honglak Lee Roger Grosse Rajesh Ranganath