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» Robust Boosting for Learning from Few Examples
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CVPR
2007
IEEE
15 years 11 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
MINENET
2005
ACM
15 years 3 months ago
Learning-based anomaly detection in BGP updates
Detecting anomalous BGP-route advertisements is crucial for improving the security and robustness of the Internet’s interdomain-routing system. In this paper, we propose an inst...
Jian Zhang, Jennifer Rexford, Joan Feigenbaum
IJCV
2008
151views more  IJCV 2008»
14 years 9 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
RECOMB
2006
Springer
15 years 10 months ago
CONTRAlign: Discriminative Training for Protein Sequence Alignment
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
Chuong B. Do, Samuel S. Gross, Serafim Batzoglou
MICAI
2007
Springer
15 years 3 months ago
Taking Advantage of the Web for Text Classification with Imbalanced Classes
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...