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ECEASST
2010
13 years 5 months ago
Self Organized Swarms for cluster preserving Projections of high-dimensional Data
: A new approach for topographic mapping, called Swarm-Organized Projection (SOP) is presented. SOP has been inspired by swarm intelligence methods for clustering and is similar to...
Alfred Ultsch, Lutz Herrmann
ESANN
2004
13 years 9 months ago
Clustering functional data with the SOM algorithm
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Fabrice Rossi, Brieuc Conan-Guez, Aïcha El Go...
ICMLA
2008
13 years 9 months ago
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...
ICCV
2009
IEEE
15 years 19 days ago
Mode-Detection via Median-Shift
Median-shift is a mode seeking algorithm that relies on computing the median of local neighborhoods, instead of the mean. We further combine median-shift with Locality Sensitive...
Lior Shapira, Shai Avidan, Ariel Shamir
EPIA
2005
Springer
14 years 1 months ago
An Extension of Self-organizing Maps to Categorical Data
Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on ...
Ning Chen, Nuno C. Marques