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» Parallelizing Feature Selection
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CVPR
2009
IEEE
16 years 11 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
CVPR
2006
IEEE
16 years 6 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
MM
2006
ACM
113views Multimedia» more  MM 2006»
15 years 10 months ago
Transductive inference using multiple experts for brushwork annotation in paintings domain
Many recent studies perform annotation of paintings based on brushwork. In these studies the brushwork is modeled indirectly as part of the annotation of high-level artistic conce...
Yelizaveta Marchenko, Tat-Seng Chua, Ramesh Jain
BIOINFORMATICS
2005
109views more  BIOINFORMATICS 2005»
15 years 4 months ago
Prediction error estimation: a comparison of resampling methods
In genomic studies, thousands of features are collected on relatively few samples. One of the goals of these studies is to build classifiers to predict the outcome of future obser...
Annette M. Molinaro, Richard Simon, Ruth M. Pfeiff...
ICFP
2009
ACM
16 years 5 months ago
Parallel concurrent ML
Concurrent ML (CML) is a high-level message-passing language that supports the construction of first-class synchronous abstractions called events. This mechanism has proven quite ...
John H. Reppy, Claudio V. Russo, Yingqi Xiao