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» Experimental Design for Variable Selection in Data Bases
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ISBI
2009
IEEE
16 years 29 days ago
Design and Study of Flux-Based Features for 3D Vascular Tracking
In this paper, we present and study two local features for the tracking of vascular structures on 3D angiograms. The first one, Flux, measures the inward gradient flux through c...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
PROMISE
2010
15 years 27 days ago
How effective is Tabu search to configure support vector regression for effort estimation?
Background. Recent studies have shown that Support Vector Regression (SVR) has an interesting potential in the field of effort estimation. However applying SVR requires to careful...
Anna Corazza, Sergio Di Martino, Filomena Ferrucci...
173
Voted
UIST
2010
ACM
15 years 4 months ago
Designing adaptive feedback for improving data entry accuracy
Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. USHER provides a theoretical, data-dri...
Kuang Chen, Joseph M. Hellerstein, Tapan S. Parikh
190
Voted
BMCBI
2005
163views more  BMCBI 2005»
15 years 6 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...
CSDA
2007
114views more  CSDA 2007»
15 years 6 months ago
Relaxed Lasso
The Lasso is an attractive regularisation method for high dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of co...
Nicolai Meinshausen