Generative Manifold Learning for the Exploration of Partially Labeled Data
نویسندگان
چکیده
منابع مشابه
Generative Manifold Learning for the Exploration of Partially Labeled Data
In many real-world application problems, the availability of data labels for supervised learning is rather limited and incompletely labeled datasets are commonplace in some of the currently most active areas of research. A manifold learning model, namely Generative Topographic Mapping (GTM), is the basis of the methods developed in the thesis reported in this paper. A variant of GTM that uses a...
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0167-8655/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.patrec.2010.09.004 ⇑ Corresponding author. Address: National Centre f okritos”, Athens, Greece. Tel.: +302106503204; fax: + E-mail address: [email protected] (A. Kri In this paper, we address the problem of learning aspect models with partially labeled data for the task of document categorization. The motivation of this w...
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ژورنال
عنوان ژورنال: Computación y Sistemas
سال: 2013
ISSN: 1405-5546
DOI: 10.13053/cys-17-4-2013-14