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» A Framework for Grid-based Neural Networks
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ICML
2008
IEEE
15 years 10 months ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio
ICANN
2007
Springer
15 years 1 months ago
A Cognitive Model That Describes the Influence of Prior Knowledge on Concept Learning
It is well known that our prior knowledge and experiences affect how we learn new concepts. Although several formal modeling attempts have been made to quantitatively describe the ...
Toshihiko Matsuka, Yasuaki Sakamoto
NN
2010
Springer
187views Neural Networks» more  NN 2010»
14 years 4 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
NC
1998
102views Neural Networks» more  NC 1998»
14 years 11 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek
JCP
2007
100views more  JCP 2007»
14 years 9 months ago
Extraction of Unique Independent Components for Nonlinear Mixture of Sources
—In this paper, a neural network solution to extract independent components from nonlinearly mixed signals is proposed. Firstly, a structurally constrained mixing model is introd...
Pei Gao, Li Chin Khor, Wai Lok Woo, Satnam Singh D...