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NIPS
2004
15 years 9 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
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...
Robert Jenssen, Deniz Erdogmus, José Carlos...
JODS
2007
102views Data Mining» more  JODS 2007»
15 years 7 months ago
Default Clustering with Conceptual Structures
This paper describes a theoretical framework for inducing knowledge from incomplete data sets. The general framework can be used with any formalism based on a lattice structure. It...
Julien Velcin, Jean-Gabriel Ganascia
DATESO
2010
148views Database» more  DATESO 2010»
15 years 5 months ago
Using Spectral Clustering for Finding Students' Patterns of Behavior in Social Networks
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
Gamila Obadi, Pavla Drázdilová, Jan ...
IGARSS
2010
15 years 5 months ago
Spatial preprocessing for endmember extraction using unsupervised clustering and orthogonal subspace projection concepts
In this paper, we develop a new spatial preprocessing strategy which can be applied prior to a spectral-based endmember extraction process for unmixing of hyperspectral data. Our ...
Gabriel Martin, Antonio J. Plaza
MLDM
2007
Springer
16 years 1 months ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...