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JMLR
2010
162views more  JMLR 2010»
15 years 1 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...
NEUROSCIENCE
2001
Springer
15 years 11 months ago
Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization
This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examin...
Joanna Bryson, Lynn Andrea Stein
ICONIP
2004
15 years 7 months ago
Neural-Evolutionary Learning in a Bounded Rationality Scenario
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
Ricardo Matsumura de Araújo, Luís C....
AROBOTS
2002
115views more  AROBOTS 2002»
15 years 6 months ago
Statistical Learning for Humanoid Robots
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata...
IJCNN
2006
IEEE
16 years 16 days ago
Model Selection via Bilevel Optimization
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...