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Elements of generative manifold learning for semi-supervised tasks
dc.contributor.author | Cruz, Raúl |
dc.contributor.author | Vellido Alcacena, Alfredo |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.date.accessioned | 2016-04-26T09:01:38Z |
dc.date.available | 2016-04-26T09:01:38Z |
dc.date.issued | 2007-01 |
dc.identifier.citation | Cruz, R., Vellido, A. "Elements of generative manifold learning for semi-supervised tasks". 2007. |
dc.identifier.uri | http://hdl.handle.net/2117/86178 |
dc.description.abstract | For many real-world application problems, the availability of data labels for supervised learning is rather limited. It is often the case that a limited number of labelled cases is accompanied by a larger number of unlabeled ones. This is the setting for semi-supervised learning, in which unsupervised approaches assist the supervised problem and viceversa. In this report, we outline some basic theoretical foundations of semi-supervised learning using models of the generative manifold-learning family. |
dc.format.extent | 15 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.other | Semi-supervised learning |
dc.subject.other | Manifold learning |
dc.subject.other | Generative methods |
dc.title | Elements of generative manifold learning for semi-supervised tasks |
dc.type | External research report |
dc.contributor.group | Universitat Politècnica de Catalunya. SOCO - Soft Computing |
dc.rights.access | Open Access |
local.identifier.drac | 1841845 |
dc.description.version | Postprint (published version) |
local.citation.author | Cruz, R.; Vellido, A. |
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