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83
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CVPR
2008
IEEE
15 years 11 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
117
Voted
DAGM
2004
Springer
15 years 1 months ago
Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features
Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We a...
Matthias Rätsch, Sami Romdhani, Thomas Vetter
85
Voted
DATAMINE
1998
145views more  DATAMINE 1998»
14 years 9 months ago
A Tutorial on Support Vector Machines for Pattern Recognition
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
Christopher J. C. Burges
INCDM
2010
Springer
308views Data Mining» more  INCDM 2010»
14 years 11 months ago
Data Mining with Neural Networks and Support Vector Machines Using the R/rminer Tool
We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs),...
Paulo Cortez
ICML
2008
IEEE
15 years 10 months ago
Optimized cutting plane algorithm for support vector machines
We have developed a new Linear Support Vector Machine (SVM) training algorithm called OCAS. Its computational effort scales linearly with the sample size. In an extensive empirica...
Sören Sonnenburg, Vojtech Franc