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» A Real Generalization of Discrete AdaBoost
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IVC
2006
187views more  IVC 2006»
13 years 7 months ago
Dynamics of facial expression extracted automatically from video
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions, including AdaBoost, support vector mach...
Gwen Littlewort, Marian Stewart Bartlett, Ian R. F...
PRL
2007
138views more  PRL 2007»
13 years 6 months ago
Ent-Boost: Boosting using entropy measures for robust object detection
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
Duy-Dinh Le, Shin'ichi Satoh
ECML
2007
Springer
14 years 1 months ago
Avoiding Boosting Overfitting by Removing Confusing Samples
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
Alexander Vezhnevets, Olga Barinova
CORR
2008
Springer
112views Education» more  CORR 2008»
13 years 7 months ago
Capacity of General Discrete Noiseless Channels
This paper concerns the capacity of the discrete noiseless channel introduced by Shannon. A sufficient condition is given for the capacity to be well-defined. For a general discre...
Georg Böcherer, Valdemar Cardoso da Rocha Jr....
ISNN
2010
Springer
13 years 5 months ago
Extension of the Generalization Complexity Measure to Real Valued Input Data Sets
Abstract. This paper studies the extension of the Generalization Complexity (GC) measure to real valued input problems. The GC measure, defined in Boolean space, was proposed as a...
Iván Gómez, Leonardo Franco, Jos&eac...