69 search results - page 3 / 14 » Learning with Distance Substitution Kernels |
KDD
2005
ACM
16 years 3 months ago
2005
ACM
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
136
click to vote
ICML
2003
IEEE
16 years 3 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...
125
click to vote
NIPS
2004
15 years 4 months ago
2004
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
132
click to vote
ICCV
2009
IEEE
16 years 8 months ago
2009
IEEE
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...
227
click to vote
COMPGEOM
2011
ACM
14 years 6 months ago
2011
ACM
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...