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» Interpretation of Trained Neural Networks by Rule Extraction
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NN
2002
Springer
114views Neural Networks» more  NN 2002»
13 years 10 months ago
Learning the parts of objects by auto-association
Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of o...
Xijin Ge, Shuichi Iwata
ICANN
2010
Springer
13 years 11 months ago
Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
Mandy Grüttner, Frank Sehnke, Tom Schaul, J&u...
ICANN
2001
Springer
14 years 3 months ago
Sparse Kernel Regressors
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization...
Volker Roth
ICASSP
2011
IEEE
13 years 2 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
NPL
2006
85views more  NPL 2006»
13 years 10 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling