DagRep.2.2.58.pdf
- Filesize: 0.81 MB
- 26 pages
Document
Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081)
Authors and all authors of the abstracts in this report
-
Part of:
Issue:
Dagstuhl Reports, Volume 2, Issue 2
Volume: Dagstuhl Reports, Volume 2
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license
- Publication Date: 2012-06-18
Cite As Get BibTex
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)
https://doi.org/10.4230/DagRep.2.2.58
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.
Subject Classification
Keywords
- Information visualization
- visual data mining
- machine learning
- nonlinear dimensionality reduction
- exploratory data analysis
Metrics
- Access Statistics
-
Total Accesses (updated on a weekly basis)
0PDF Downloads