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» The baldwin effect in developing neural networks
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JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
IJON
2008
168views more  IJON 2008»
13 years 7 months ago
Spatial relationship representation for visual object searching
Image representation has been a key issue in vision research for many years. In order to represent various local image patterns or objects effectively, it is important to study th...
Jun Miao, Lijuan Duan, Laiyun Qing, Wen Gao, Xilin...
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
ICANN
2010
Springer
13 years 7 months ago
On the Fringe of Awareness: The Glance-Look Model of Attention-Emotion Interactions
In previous work, we have developed a "Glance-Look" model, which has replicated a broad profile of data on the semantic Attentional Blink (AB) task and characterized how ...
Li Su, Philip Barnard, Howard Bowman
EC
2000
241views ECommerce» more  EC 2000»
13 years 7 months ago
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
To successfully apply evolutionary algorithms to the solution of increasingly complex problems, we must develop effective techniques for evolving solutions in the form of interact...
Mitchell A. Potter, Kenneth A. De Jong