54 search results - page 4 / 11 » Semi-supervised learning by locally linear embedding in kern... |
ICML
2003
IEEE
15 years 10 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
14 years 8 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...
104
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ICMLC
2005
Springer
15 years 3 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
13 years 5 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...
102
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DIS
2007
Springer
15 years 3 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...