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» The structure of intrinsic complexity of learning
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IVC
2007
184views more  IVC 2007»
13 years 7 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
AGI
2008
13 years 9 months ago
Cognitive Primitives for Automated Learning
Artificial Intelligence deals with the automated simulation of human intelligent behavior. Various aspects of human faculties are tackled using computational models. It is clear th...
Sudharsan Iyengar
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
13 years 11 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
WORDS
2003
IEEE
14 years 23 days ago
Using Co-ordinated Atomic Actions for Building Complex Web Applications: A Learning Experience
This paper discusses some of the typical characteristics of modern Web applications and analyses some of the problems the developers of such systems have to face. One of such type...
Avelino F. Zorzo, Panayiotis Periorellis, Alexande...
CEC
2010
IEEE
13 years 8 months ago
Two novel Ant Colony Optimization approaches for Bayesian network structure learning
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Yanghui Wu, John A. W. McCall, David W. Corne