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» Using model knowledge for learning inverse dynamics
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144
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GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 4 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
151
Voted
AAAI
1997
15 years 5 months ago
Building Concept Representations from Reusable Components
Our goal is to build knowledge-based systems capable of answering a wide variety of questions, including questions that are unanticipated when the knowledge base is built. For sys...
Peter Clark, Bruce W. Porter
133
Voted
ECAL
2007
Springer
15 years 10 months ago
Neuroevolution of Agents Capable of Reactive and Deliberative Behaviours in Novel and Dynamic Environments
Both reactive and deliberative qualities are essential for a good action selection mechanism. We present a model that embodies a hybrid of two very different neural network archit...
Edward Robinson, Timothy Ellis, Alastair Channon
WWW
2004
ACM
16 years 4 months ago
Enhancing the SCORM metadata model
Nowadays, the leading e-learning platforms are converging towards standardization. This paper presents an extension to the SCORM, today's most well acclaimed e-learning stand...
David Simões, Nuno Horta, Rui Luís
145
Voted
ICML
2008
IEEE
16 years 4 months ago
Gaussian process product models for nonparametric nonstationarity
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
Ryan Prescott Adams, Oliver Stegle