910 search results - page 21 / 182 » Parallel Support Vector Machines: The Cascade SVM |
PR
2007
13 years 8 months ago
2007
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
JMLR
2008
13 years 8 months ago
2008
This paper investigates statistical performances of Support Vector Machines (SVM) and considers the problem of adaptation to the margin parameter and to complexity. In particular ...
CVPR
2005
IEEE
14 years 10 months ago
2005
IEEE
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
ECAI
2004
Springer
14 years 2 months ago
2004
Springer
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
ECML
2006
Springer
13 years 10 months ago
2006
Springer
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...