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» Learning Hierarchical Shape Models from Examples
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SIGIR
2008
ACM
13 years 7 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
COGSCI
2010
103views more  COGSCI 2010»
13 years 8 months ago
A Computational Account of the Development of the Generalization of Shape Information
Abecassis, Sera, Yonas, and Schwade (2001) have shown that young children represent shapes more metrically, and perhaps more holistically, than do older children and adults. How d...
Leonidas A. A. Doumas, John E. Hummel
IDA
2003
Springer
14 years 1 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
BMCBI
2010
143views more  BMCBI 2010»
13 years 8 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli

Tutorial
1113views
12 years 4 months ago
Snakes, Shapes, and Gradient vector flow
Active contours, or snakes, are computer-generated curves that move within images to find object boundaries. Its 3D version is often known as deformable models or active surfaces ...