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Documents authored by Verleysen, Michel

Document
DOI: 10.4230/DagRep.2.2.58
Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081)

Authors: Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, and Stefan Wrobel

Published in: Dagstuhl Reports, Volume 2, Issue 2 (2012)

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.
Cite as

Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, and Stefan Wrobel. Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081). In Dagstuhl Reports, Volume 2, Issue 2, pp. 58-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@Article{keim_et_al:DagRep.2.2.58,
  author =	{Keim, Daniel A. and Rossi, Fabrice and Seidl, Thomas and Verleysen, Michel and Wrobel, Stefan},
  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 =	{Keim, Daniel A. and Rossi, Fabrice and Seidl, Thomas and Verleysen, Michel and Wrobel, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.2.2.58},
  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}
}
Document
DOI: 10.4230/DagSemProc.07131.1
07131 Abstracts Collection – Similarity-based Clustering and its Application to Medicine and Biology

Authors: Michael Biehl, Barbara Hammer, Michel Verleysen, and Thomas Villmann

Published in: Dagstuhl Seminar Proceedings, Volume 7131, Similarity-based Clustering and its Application to Medicine and Biology (2007)

Abstract
From 25.03. to 30.03.2007, the Dagstuhl Seminar 07131 ``Similarity-based Clustering and its Application to Medicine and Biology'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Michael Biehl, Barbara Hammer, Michel Verleysen, and Thomas Villmann. 07131 Abstracts Collection – Similarity-based Clustering and its Application to Medicine and Biology. In Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings, Volume 7131, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{biehl_et_al:DagSemProc.07131.1,
  author =	{Biehl, Michael and Hammer, Barbara and Verleysen, Michel and Villmann, Thomas},
  title =	{{07131 Abstracts Collection – Similarity-based Clustering and its Application to Medicine and Biology}},
  booktitle =	{Similarity-based Clustering and its Application to Medicine and Biology},
  pages =	{1--12},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7131},
  editor =	{Michael Biehl and Barbara Hammer and Michel Verleysen and Thomas Villmann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07131.1},
  URN =		{urn:nbn:de:0030-drops-11190},
  doi =		{10.4230/DagSemProc.07131.1},
  annote =	{Keywords: Similarity-based clustering and classification, prototype-based classifiers, self-organisation, SOM, learning vector quantization, medical diagnosis, bioinformatics}
}
Document
DOI: 10.4230/DagSemProc.07131.2
07131 Summary – Similarity-based Clustering and its Application to Medicine and Biology

Authors: Michael Biehl, Barbara Hammer, Michel Verleysen, and Thomas Villmann

Published in: Dagstuhl Seminar Proceedings, Volume 7131, Similarity-based Clustering and its Application to Medicine and Biology (2007)

Abstract
This paper summarizes presentations, discussions, and results of the Dagstuhl seminar.
Cite as

Michael Biehl, Barbara Hammer, Michel Verleysen, and Thomas Villmann. 07131 Summary – Similarity-based Clustering and its Application to Medicine and Biology. In Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings, Volume 7131, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{biehl_et_al:DagSemProc.07131.2,
  author =	{Biehl, Michael and Hammer, Barbara and Verleysen, Michel and Villmann, Thomas},
  title =	{{07131 Summary – Similarity-based Clustering and its Application to Medicine and Biology}},
  booktitle =	{Similarity-based Clustering and its Application to Medicine and Biology},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7131},
  editor =	{Michael Biehl and Barbara Hammer and Michel Verleysen and Thomas Villmann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07131.2},
  URN =		{urn:nbn:de:0030-drops-11177},
  doi =		{10.4230/DagSemProc.07131.2},
  annote =	{Keywords: Clustering, bioinformatics, medicine}
}
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