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» The Convergence Rate of AdaBoost
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CVPR
2005
IEEE
14 years 11 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
ICML
2008
IEEE
14 years 10 months ago
Random classification noise defeats all convex potential boosters
A broad class of boosting algorithms can be interpreted as performing coordinate-wise gradient descent to minimize some potential function of the margins of a data set. This class...
Philip M. Long, Rocco A. Servedio
CIARP
2009
Springer
14 years 1 months ago
Pigmented Skin Lesions Classification Using Dermatoscopic Images
In this paper we propose a machine learning approach to classify melanocytic lesions in malignant and benign from dermatoscopic images. The image database is composed of 433 benign...
Germán Capdehourat, Andrés Corez, An...
ICML
2003
IEEE
14 years 10 months ago
Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization
Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to S...
Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Ha...
CVPR
2001
IEEE
14 years 11 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones