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» Making inferences with small numbers of training sets
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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
14 years 11 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
ICSE
2010
IEEE-ACM
15 years 1 months ago
DETERMIN: inferring likely deterministic specifications of multithreaded programs
The trend towards multicore processors and graphic processing units is increasing the need for software that can take advantage of parallelism. Writing correct parallel programs u...
Jacob Burnim, Koushik Sen
BMCBI
2007
148views more  BMCBI 2007»
14 years 12 months ago
BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes
Background: Overlapping genes (OGs) in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of seque...
Yingqin Luo, Cong Fu, Da-Yong Zhang, Kui Lin
AAAI
1998
15 years 1 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
CISIS
2009
IEEE
14 years 9 months ago
Simultaneous Background/Foreground Segmentation and Contour Smoothing with Level Set Based Partial Differential Equation for Int
In this paper, we propose a level set based energy functional, the minimization of which results in simultaneous background modeling, foreground segmentation, and contour smoothin...
Suk Ho Lee, Nam-seok Choi, Byung-Gook Lee, Moon Gi...