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Unfolding the Manifold in Generative Topographic Mapping
dc.contributor.author | Cruz Barbosa, Raúl |
dc.contributor.author | Vellido Alcacena, Alfredo |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.date.accessioned | 2010-10-07T09:57:36Z |
dc.date.available | 2010-10-07T09:57:36Z |
dc.date.created | 2008-09 |
dc.date.issued | 2008-09 |
dc.identifier.citation | Cruz, R.; Vellido, A. Unfolding the Manifold in Generative Topographic Mapping. "Lecture notes in computer science", Setembre 2008, vol. 5271, p. 392-399. |
dc.identifier.issn | 0302-9743 |
dc.identifier.uri | http://hdl.handle.net/2117/9511 |
dc.description.abstract | Generative Topographic Mapping (GTM) is a probabilistic latent variable model for multivariate data clustering and visualization. It tries to capture the relevant data structure by defining a low-dimensional manifold embedded in the high-dimensional data space. This requires the assumption that the data can be faithfully represented by a manifold of much lower dimension than that of the observed space. Even when this assumption holds, the approximation of the data may, for some datasets, require plenty of folding, resulting in an entangled manifold and in breaches of topology preservation that would hamper data visualization and cluster definition. This can be partially avoided by modifying the GTM learning procedure so as to penalize divergences between the Euclidean distances from the data to the model prototypes and the corresponding geodesic distances along the manifold. We define and assess this strategy, comparing it to the performance of the standard GTM, using several artificial datasets. |
dc.format.extent | 8 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
dc.subject.lcsh | Generative Topographic Mapping (GTM) |
dc.title | Unfolding the Manifold in Generative Topographic Mapping |
dc.type | Article |
dc.contributor.group | Universitat Politècnica de Catalunya. SOCO - Soft Computing |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 1623394 |
dc.description.version | Postprint (published version) |
local.citation.author | Cruz, R.; Vellido, A. |
local.citation.publicationName | Lecture notes in computer science |
local.citation.volume | 5271 |
local.citation.startingPage | 392 |
local.citation.endingPage | 399 |
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