619 search results - page 52 / 124 » A Kernel Method for the Two-Sample Problem |
115
Voted
CVPR
2003
IEEE
16 years 4 months ago
2003
IEEE
It is now common practice in machine vision to define the variability in an object's appearance in a factored manner, as a combination of shape and texture transformations. I...
121
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NIPS
2008
15 years 4 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
135
Voted
ICML
2009
IEEE
16 years 3 months ago
2009
IEEE
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
135
Voted
NIPS
2001
15 years 4 months ago
2001
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
113
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PR
2006
2006
Correspondence matching using kernel principal components analysis and label consistency constraints
15 years 2 months ago
This paper investigates spectral approaches to the problem of point pattern matching. We make two contributions. First, we consider rigid point-set alignment. Here we show how ker...