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IJCNN
2006
IEEE
14 years 2 months ago
Global Reinforcement Learning in Neural Networks with Stochastic Synapses
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
Xiaolong Ma, Konstantin Likharev
ANNPR
2008
Springer
13 years 10 months ago
Partial Discriminative Training of Neural Networks for Classification of Overlapping Classes
In applications such as character recognition, some classes are heavily overlapped but are not necessarily to be separated. For classification of such overlapping classes, either d...
Cheng-Lin Liu
ICML
1995
IEEE
14 years 9 months ago
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Justine Blackmore, Risto Miikkulainen
ICMLA
2009
13 years 6 months ago
Application of Artificial Neural Network (ANN) Method to Exergy Analysis of Thermodynamic Systems
Exergy is a way to sustainable development and may be defined as the maximum theoretical useful work, while exergy analysis identifies the sources, the magnitude and the causes of...
Yilmaz Yoru, T. Hikmet Karakoc, Arif Hepbasli
ANNES
1995
14 years 11 days ago
The Development of Holte's 1R Classifier
The 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the metho...
Craig G. Nevill-Manning, Geoffrey Holmes, Ian H. W...