Mixed membership stochastic blockmodels
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Mixed membership stochastic blockmodels
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| Id. |
25662918 |
| Titulo |
Mixed membership stochastic blockmodels |
| Autor(es) |
Airoldi, Edoardo M
Blei, David M
Fienberg, Stephen E
Xing, Eric P
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| Localización |
http://arxiv.org/abs/0705.4485
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| Versión |
1.0 |
| Estado |
Final
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| Descripción |
Observations consisting of measurements on relationships for pairs of objects
arise in many settings, such as protein interaction and gene regulatory
networks, collections of author-recipient email, and social networks. Analyzing
such data with probabilisic models can be delicate because the simple
exchangeability assumptions underlying many boilerplate models no longer hold.
In this paper, we describe a latent variable model of such data called the
mixed membership stochastic blockmodel. This model extends blockmodels for
relational data to ones which capture mixed membership latent relational
structure, thus providing an object-specific low-dimensional representation. We
develop a general variational inference algorithm for fast approximate
posterior inference. We explore applications to social and protein interaction
networks.
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| Palabras clave |
Statistics - Methodology
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| Tipo de recurso |
Texto Narrativo
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| Tipo de Interactividad |
Expositivo
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| Nivel de Interactividad |
muy bajo
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| Audiencia |
Estudiante
Profesor
Autor
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| Estructura |
Atomic |
| Coste |
no
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| Copyright |
sí
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| Requerimientos técnicos |
Browser: Any
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| Fecha de contribución |
26-jun-2007 |
| Contacto |
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