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SIGIR
2008
ACM
15 years 6 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
BMCBI
2005
90views more  BMCBI 2005»
15 years 6 months ago
TMB-Hunt: An amino acid composition based method to screen proteomes for beta-barrel transmembrane proteins
Background: Beta-barrel transmembrane (bbtm) proteins are a functionally important and diverse group of proteins expressed in the outer membranes of bacteria (both gram negative a...
Andrew G. Garrow, Alison Agnew, David R. Westhead
CVPR
2009
IEEE
17 years 1 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
CVPR
2005
IEEE
16 years 8 months ago
A SIFT Descriptor with Global Context
Matching points between multiple images of a scene is a vital component of many computer vision tasks. Point matching involves creating a succinct and discriminative descriptor fo...
Eric N. Mortensen, Hongli Deng, Linda G. Shapiro
CVPR
2006
IEEE
16 years 8 months ago
Spatial Divide and Conquer with Motion Cues for Tracking through Clutter
Tracking can be considered a two-class classification problem between the foreground object and its surrounding background. Feature selection to better discriminate object from ba...
Zhaozheng Yin, Robert T. Collins