4947 search results - page 113 / 990 » Learning Module Networks |
111
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GECCO
2004
Springer
15 years 7 months ago
2004
Springer
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canon...
126
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ICML
2004
IEEE
16 years 3 months ago
2004
IEEE
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
113
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IJON
2007
15 years 2 months ago
2007
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples and thereby increase speed a...
113
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ISCAS
2003
IEEE
15 years 7 months ago
2003
IEEE
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
94
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ICANN
2005
Springer
15 years 7 months ago
2005
Springer
This paper aims to propose an extension of SOMs called an “SOM of SOMs,” or SOM¾ , in which the mapped objects are self-organizing maps themselves. In SOM¾ , each nodal unit ...