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Learning in the context of very high dimensional data (Dagstuhl Seminar 11341) Biehl, Michael Hammer, Barbara Merényi, Erzsébet Sperduti, Alessandro Villman, Thomas Curse of dimensionality Dimensionality reduction Regularization Deep learning Visualization This report documents the program and the outcomes of Dagstuhl Seminar 11341 "Learning in the context of very high dimensional data". The aim of the seminar was to bring together researchers who develop, investigate, or apply machine learning methods for very high dimensional data to advance this important field of research. The focus was be on broadly applicable methods and processing pipelines, which offer efficient solutions for high-dimensional data analysis appropriate for a wide range of application scenarios. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Michael Biehl and Barbara Hammer and Erzsébet Merényi and Alessandro Sperduti and Thomas Villman 2011 Is Part Of Dagstuhl Reports, Volume 1, Issue 8 (2011) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.1.8.67 urn:nbn:de:0030-drops-33125 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.1.8.67 eng https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode