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CMOT
1999
143views more  CMOT 1999»
15 years 6 months ago
Structural Learning: Attraction and Conformity in Task-Oriented Groups
This study extends previous research that showed how informal social sanctions can backfire when members prefer friendship over enforcement of group norms. We use a type of neural...
James A. Kitts, Michael W. Macy, Andreas Flache
CISIS
2010
IEEE
15 years 5 months ago
Modeling of Stress-induced Regulatory Cascades Involving Transcription Factor Dimers
Regulatory cascades consisting of stress-induced gene modules and their transcriptional regulators were recently identified and quantitatively modeled using Artificial Neural Netwo...
Maria Manioudaki, Panayiota Poirazi
165
Voted
IJCNN
2006
IEEE
16 years 1 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002
GECCO
2009
Springer
15 years 11 months ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
231
Voted
ESANN
2007
15 years 8 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann