Probabilistic abductive logic programming using Dirichlet priors

Probabilistic programming is an area of research that aims to develop general inference algorithms for probabilistic models expressed as probabilistic programs whose execution corresponds to inferring the parameters of those models. In this paper, we introduce a probabilistic programming language (P...

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Bibliographic Details
Published in:	International journal of approximate reasoning Vol. 78; pp. 223 - 240
Main Authors:	Turliuc, Calin Rares, Dickens, Luke, Russo, Alessandra, Broda, Krysia
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.11.2016
Subjects:	Abductive logic programming Algorithms Dirichlet problem Inference Latent Dirichlet allocation Logic programming Markov Chain Monte Carlo Mathematical models Probabilistic methods Probabilistic programming Probability theory Repeated insertion model Sampling Abductive logic programming Repeated insertion model Latent Dirichlet allocation Markov Chain Monte Carlo Probabilistic programming
ISSN:	0888-613X, 1873-4731
Online Access:	Get full text
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