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ICML
2005
IEEE
14 years 9 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ACCV
2007
Springer
14 years 4 days ago
A Cascade of Feed-Forward Classifiers for Fast Pedestrian Detection
We develop a method that can detect humans in a single image based on a new cascaded structure. In our approach, both the rectangle features and 1-D edge-orientation features are e...
Yu-Ting Chen, Chu-Song Chen
SIGMOD
2007
ACM
159views Database» more  SIGMOD 2007»
14 years 8 months ago
Boosting topic-based publish-subscribe systems with dynamic clustering
We consider in this paper a class of Publish-Subscribe (pub-sub) systems called topic-based systems, where users subscribe to topics and are notified on events that belong to thos...
Tova Milo, Tal Zur, Elad Verbin
CVPR
2005
IEEE
14 years 10 months ago
Boosting Saliency in Color Image Features
The aim of salient point detection is to find distinctive events in images. Salient features are generally determined from the local differential structure of images. They focus o...
Joost van de Weijer, Theo Gevers
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy