Recent advances in nonlinear dimensionality reduction, manifold and topological learning

Axel Wismüller, Michel Verleysen, Michael Aupetit, John A. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

52 Citations (Scopus)

Abstract

The ever-growing amount of data stored in digital databases raises the question of how to organize and extract useful knowledge. This paper outlines some current developments in the domains of dimensionality reduction, manifold learning, and topological learning. Several aspects are dealt with, ranging from novel algorithmic approaches to their realworld applications. The issue of quality assessment is also considered and progress in quantitive as well as visual crieria is reported.

Original languageEnglish
Title of host publicationProceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010
Pages71-80
Number of pages10
Publication statusPublished - 2010
Externally publishedYes
Event18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2010 - Bruges, Belgium
Duration: 28 Apr 201030 Apr 2010

Publication series

NameProceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010

Conference

Conference18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2010
Country/TerritoryBelgium
CityBruges
Period28/04/1030/04/10

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