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CORR
2011
Springer
13 years 2 months ago
2011
Springer
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
BIBM
2009
IEEE
14 years 2 months ago
2009
IEEE
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
Object recognition accuracy can be improved when information from multiple views is integrated, but information in each view can often be highly redundant. We consider the problem...