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ICANN
2010
Springer
13 years 6 months ago
Discovery of Exogenous Variables in Data with More Variables Than Observations
Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations. However, modern datasets including gene expres...
Yasuhiro Sogawa, Shohei Shimizu, Aapo Hyvärin...
BMCBI
2008
171views more  BMCBI 2008»
13 years 5 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
13 years 10 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs
CVPR
2006
IEEE
14 years 6 months ago
Escaping local minima through hierarchical model selection: Automatic object discovery, segmentation, and tracking in video
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...
Nebojsa Jojic, John M. Winn, Larry Zitnick
BMCBI
2008
138views more  BMCBI 2008»
13 years 5 months ago
Inference of haplotypic phase and missing genotypes in polyploid organisms and variable copy number genomic regions
Background: The power of haplotype-based methods for association studies, identification of regions under selection, and ancestral inference, is well-established for diploid organ...
Shu-Yi Su, Jonathan White, David J. Balding, Lachl...