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» The Rate of Convergence of AdaBoost
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NIPS
2001
8 years 8 months ago
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
Paul A. Viola, Michael J. Jones
ALT
2004
Springer
9 years 4 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe
IWBRS
2005
Springer
168views Biometrics» more  IWBRS 2005»
9 years 27 days ago
Gabor Feature Selection for Face Recognition Using Improved AdaBoost Learning
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
TSMC
2008
172views more  TSMC 2008»
8 years 7 months ago
AdaBoost-Based Algorithm for Network Intrusion Detection
Abstract--Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security sy...
Weiming Hu, Wei Hu, Stephen J. Maybank
CVPR
2006
IEEE
9 years 9 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...
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