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» Experimental Design for Variable Selection in Data Bases
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PAKDD
2007
ACM
203views Data Mining» more  PAKDD 2007»
15 years 12 months ago
Grammar Guided Genetic Programming for Flexible Neural Trees Optimization
Abstract. In our previous studies, Genetic Programming (GP), Probabilistic Incremental Program Evolution (PIPE) and Ant Programming (AP) have been used to optimal design of Flexibl...
Peng Wu, Yuehui Chen
CSDA
2007
106views more  CSDA 2007»
15 years 5 months ago
Parsimonious additive models
A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
EOR
2007
85views more  EOR 2007»
15 years 5 months ago
Reject inference, augmentation, and sample selection
Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Al...
John Banasik, Jonathan Crook
ISLPED
2010
ACM
202views Hardware» more  ISLPED 2010»
15 years 6 months ago
MODEST: a model for energy estimation under spatio-temporal variability
Estimation of static and dynamic energy of caches is critical for high-performance low-power designs. Commercial CAD tools performing energy estimation statically are not aware of...
Shrikanth Ganapathy, Ramon Canal, Antonio Gonz&aac...
DAC
2008
ACM
16 years 6 months ago
TuneFPGA: post-silicon tuning of dual-Vdd FPGAs
Modern CMOS manufacturing processes have significant variability, which necessitates guard banding to achieve reasonable yield. We study an FPGA architecture with a dual voltage s...
Stephen Bijansky, Adnan Aziz