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» Classifying Problems into Complexity Classes
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105
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BMCBI
2007
138views more  BMCBI 2007»
15 years 27 days ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
JMIV
2006
124views more  JMIV 2006»
15 years 22 days ago
Segmentation of a Vector Field: Dominant Parameter and Shape Optimization
Vector field segmentation methods usually belong to either of three classes: methods which segment regions homogeneous in direction and/or norm, methods which detect discontinuiti...
Tristan Roy, Eric Debreuve, Michel Barlaud, Gilles...
112
Voted
MICCAI
2007
Springer
16 years 1 months ago
Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree
Abstract. Automatic delineation and robust measurement of fetal anatomical structures in 2D ultrasound images is a challenging task due to the complexity of the object appearance, ...
Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dor...
92
Voted
WWW
2005
ACM
16 years 1 months ago
An experimental study on large-scale web categorization
Taxonomies of the Web typically have hundreds of thousands of categories and skewed category distribution over documents. It is not clear whether existing text classification tech...
Tie-Yan Liu, Yiming Yang, Hao Wan, Qian Zhou, Bin ...
ICML
2007
IEEE
16 years 1 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...