54 search results - page 4 / 11 » Semi-supervised learning by locally linear embedding in kern... |
ICML
2003
IEEE
14 years 6 months ago
2003
IEEE
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
SSPR
2010
Springer
13 years 3 months ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
ICMLC
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...
DIS
2007
Springer
13 years 11 months ago
2007
Springer
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...