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» Neural Networks and Complexity Theory
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ICANN
2009
Springer
15 years 9 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
IWANN
2001
Springer
15 years 9 months ago
Using Contextual Information to Selectively Adjust Preprocessing Parameters
Abstract. It is generally accepted that some of the problems and ambiguities at the low level of processing can not be resolved without taking into account contextual expectations....
Predrag Neskovic, Leon N. Cooper
HIS
2004
15 years 5 months ago
Classification Ensembles for Shaft Test Data: Empirical Evaluation
: A-scans from ultrasonic testing of long shafts are complex signals. The discrimination of different types of echoes is of importance for non-destructive testing and equipment mai...
Kyungmi Lee, Vladimir Estivill-Castro
ICMCS
2010
IEEE
211views Multimedia» more  ICMCS 2010»
15 years 5 months ago
Heterogenesis: Collectively emergent autonomy
Heterogenesis is an interactive sound and tactile installation consisting of a group of autonomous artificial agents that collectively generate and evolve a soundscape in response...
Carlos Castellanos, Diane Gromala, Philippe Pasqui...
EAAI
2007
90views more  EAAI 2007»
15 years 4 months ago
AI techniques in modelling, assignment, problem solving and optimization
This paper recapitulates the results of a long research on a family of artificial intelligence (AI) methods—relying on, e.g., artificial neural networks and search techniques...
Zsolt János Viharos, Zsolt Kemény