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» Evolutionary Regression Modeling with Active Learning: An Ap...
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NC
2006
132views Neural Networks» more  NC 2006»
13 years 5 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu
ICAC
2006
IEEE
13 years 11 months ago
Learning Application Models for Utility Resource Planning
Abstract— Shared computing utilities allocate compute, network, and storage resources to competing applications on demand. An awareness of the demands and behaviors of the hosted...
Piyush Shivam, Shivnath Babu, Jeffrey S. Chase
CSL
2008
Springer
13 years 5 months ago
A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Andreas Vlachos
JSS
2008
317views more  JSS 2008»
13 years 5 months ago
Predicting defect-prone software modules using support vector machines
Effective prediction of defectprone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Supp...
Karim O. Elish, Mahmoud O. Elish
GECCO
2003
Springer
158views Optimization» more  GECCO 2003»
13 years 10 months ago
Active Control of Thermoacoustic Instability in a Model Combustor with Neuromorphic Evolvable Hardware
Continuous Time Recurrent Neural Networks (CTRNNs) have previously been proposed as an enabling paradigm for evolving analog electrical circuits to serve as controllers for physica...
John C. Gallagher, Saranyan Vigraham