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When quoting this document, please refer to the following
DOI: 10.4230/DagRep.2.2.58
URN: urn:nbn:de:0030-drops-35064
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2012/3506/
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Keim, Daniel A. ; Rossi, Fabrice ; Seidl, Thomas ; Verleysen, Michel ; Wrobel, Stefan
Weitere Beteiligte (Hrsg. etc.): Daniel A. Keim and Fabrice Rossi and Thomas Seidl and Michel Verleysen and Stefan Wrobel

Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081)

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dagrep_v002_i002_p058_s12081.pdf (0.8 MB)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 12081
``Information Visualization, Visual Data Mining and Machine Learning''. The
aim of the seminar was to tighten the links between the information
visualisation community and the machine learning community in order to explore
how each field can benefit from the other and how to go beyond current
hybridization successes.

BibTeX - Entry

@Article{keim_et_al:DR:2012:3506,
  author =	{Daniel A. Keim and Fabrice Rossi and Thomas Seidl and Michel Verleysen and Stefan Wrobel},
  title =	{{Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081)}},
  pages =	{58--83},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2012},
  volume =	{2},
  number =	{2},
  editor =	{Daniel A. Keim and Fabrice Rossi and Thomas Seidl and Michel Verleysen and Stefan Wrobel},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2012/3506},
  URN =		{urn:nbn:de:0030-drops-35064},
  doi =		{10.4230/DagRep.2.2.58},
  annote =	{Keywords: Information visualization, visual data mining, machine learning, nonlinear dimensionality reduction, exploratory data analysis}
}

Keywords: Information visualization, visual data mining, machine learning, nonlinear dimensionality reduction, exploratory data analysis
Collection: Dagstuhl Reports, Volume 2, Issue 2
Issue Date: 2012
Date of publication: 18.06.2012

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