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» The Kernel Trick for Distances
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COMPGEOM
2011
ACM
12 years 11 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
ICML
2008
IEEE
14 years 8 months ago
A reproducing kernel Hilbert space framework for pairwise time series distances
A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...
ICPR
2002
IEEE
14 years 17 days ago
Tangent Distance Kernels for Support Vector Machines
When dealing with pattern recognition problems one encounters different types of a-priori knowledge. It is important to incorporate such knowledge into the classification method ...
Bernard Haasdonk, Daniel Keysers
ESANN
2007
13 years 9 months ago
Clustering a medieval social network by SOM using a kernel based distance measure
Abstract. In order to explore the social organization of a medieval peasant community before the Hundred Years’ War, we propose the use of an adaptation of the well-known Kohonen...
Nathalie Villa, Romain Boulet
ICCV
2009
IEEE
1824views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Beyond the Euclidean distance: Creating effective visual codebooks using the histogram intersection kernel
Common visual codebook generation methods used in a Bag of Visual words model, e.g. k-means or Gaussian Mixture Model, use the Euclidean distance to cluster features into visual...
Jianxin Wu, James M. Rehg