565 search results - page 2 / 113 » A Generalized Quadratic Loss for Support Vector Machines |
TIT
2002
13 years 4 months ago
2002
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...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Straightforward classification using kernelized SVMs requires evaluating the kernel for a test vector and each of the support vectors. For a class of kernels we show that one can ...
PKDD
2010
Springer
13 years 3 months ago
2010
Springer
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
NIPS
2003
13 years 6 months ago
2003
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
ICNC
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...