Learning Bayesian networks from data by the incremental compilation of new network polynomials

Benjumeda Barquita, Marco (2014). Learning Bayesian networks from data by the incremental compilation of new network polynomials. Tesis (Master), Facultad de Informática (UPM) [antigua denominación].

Descripción

Título: Learning Bayesian networks from data by the incremental compilation of new network polynomials
Autor/es:
  • Benjumeda Barquita, Marco
Director/es:
  • Bielza Lozoya, Maria Concepcion
  • Larrañaga, Pedro
Tipo de Documento: Tesis (Master)
Título del máster: Inteligencia Artificial
Fecha: 25 Octubre 2014
Materias:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Licencias Creative Commons: Ninguna

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Resumen

Probabilistic graphical models are a huge research field in artificial intelligence nowadays. The scope of this work is the study of directed graphical models for the representation of discrete distributions. Two of the main research topics related to this area focus on performing inference over graphical models and on learning graphical models from data. Traditionally, the inference process and the learning process have been treated separately, but given that the learned models structure marks the inference complexity, this kind of strategies will sometimes produce very inefficient models. With the purpose of learning thinner models, in this master thesis we propose a new model for the representation of network polynomials, which we call polynomial trees. Polynomial trees are a complementary representation for Bayesian networks that allows an efficient evaluation of the inference complexity and provides a framework for exact inference. We also propose a set of methods for the incremental compilation of polynomial trees and an algorithm for learning polynomial trees from data using a greedy score+search method that includes the inference complexity as a penalization in the scoring function.

Más información

ID de Registro: 35308
Identificador DC: http://oa.upm.es/35308/
Identificador OAI: oai:oa.upm.es:35308
Depositado por: Marco Alberto Benjumeda Barquita
Depositado el: 21 May 2015 12:56
Ultima Modificación: 08 Feb 2016 11:47
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