@InProceedings{engel_et_al:OASIcs.VLUDS.2011.135,
  author =	{Engel, Daniel and H\"{u}ttenberger, Lars and Hamann, Bernd},
  title =	{{A Survey of Dimension Reduction Methods for High-dimensional Data Analysis and Visualization}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{135--149},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Garth, Christoph and Middel, Ariane and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2011.135},
  URN =		{urn:nbn:de:0030-drops-37475},
  doi =		{10.4230/OASIcs.VLUDS.2011.135},
  annote =	{Keywords: high-dimensional, multivariate data, dimension reduction, manifold learning}
}