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» Learning to learn with the informative vector machine
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ICCV
2011
IEEE
14 years 4 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
BMCBI
2007
147views more  BMCBI 2007»
15 years 4 months ago
Comparative analysis of long DNA sequences by per element information content using different contexts
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...
COLT
2007
Springer
15 years 11 months ago
Resource-Bounded Information Gathering for Correlation Clustering
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
Pallika Kanani, Andrew McCallum
ISDA
2009
IEEE
15 years 11 months ago
Measures for Unsupervised Fuzzy-Rough Feature Selection
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
Neil MacParthalain, Richard Jensen
ECCV
2010
Springer
15 years 10 months ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...