6 search results - page 1 / 2 » The Laplacian PDF Distance: A Cost Function for Clustering i... |
NIPS
2004
13 years 6 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...
IJCNN
2006
IEEE
13 years 11 months ago
2006
IEEE
— Recent work has revealed a close connection between certain information theoretic divergence measures and properties of Mercer kernel feature spaces. Specifically, it has been...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
PRL
2008
13 years 4 months ago
2008
This article introduces a scheme for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring groups in the data. T...