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» How boosting the margin can also boost classifier complexity
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IWANN
2005
Springer
13 years 10 months ago
Balanced Boosting with Parallel Perceptrons
Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many ...
Iván Cantador, José R. Dorronsoro
DAGM
2003
Springer
13 years 10 months ago
Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection
Recently Viola et al. have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce and empirically analysis ...
Rainer Lienhart, Alexander Kuranov, Vadim Pisarevs...
ASPLOS
1992
ACM
13 years 9 months ago
Efficient Superscalar Performance Through Boosting
The foremost goal of superscalar processor design is to increase performance through the exploitation of instruction-level parallelism (ILP). Previous studies have shown that spec...
Michael D. Smith, Mark Horowitz, Monica S. Lam
TIT
2002
164views more  TIT 2002»
13 years 4 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
CVPR
2009
IEEE
14 years 11 months ago
Reducing JointBoost-Based Multiclass Classification to Proximity Search
Boosted one-versus-all (OVA) classifiers are commonly used in multiclass problems, such as generic object recognition, biometrics-based identification, or gesture recognition. Join...
Alexandra Stefan (University of Texas at Arlington...