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JMLR
2012
11 years 10 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
ALT
2011
Springer
12 years 7 months ago
On the Expressive Power of Deep Architectures
Deep architectures are families of functions corresponding to deep circuits. Deep Learning algorithms are based on parametrizing such circuits and tuning their parameters so as to ...
Yoshua Bengio, Olivier Delalleau
SIGGRAPH
2000
ACM
13 years 12 months ago
Deep shadow maps
We introduce deep shadow maps, a technique that produces fast, high-quality shadows for primitives such as hair, fur, and smoke. Unlike traditional shadow maps, which store a sing...
Tom Lokovic, Eric Veach
ASWC
2008
Springer
13 years 9 months ago
Deep Semantic Mapping between Functional Taxonomies for Interoperable Semantic Search
This paper discusses ontology mapping between two taxonomies of functions of artifacts for the engineering knowledge management. The mapping is of two ways and has been manually es...
Yoshinobu Kitamura, Sho Segawa, Munehiko Sasajima,...
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 2 months ago
A Deep Non-linear Feature Mapping for Large-Margin kNN Classification
Martin Renqiang Min, David A. Stanley, Zineng Yuan...