Online Bayesian inference for the parameters of PRISM programs
type: Item
instance of: scholarly article
title: Online Bayesian inference for the parameters of PRISM programs
zbMATH Open document ID: 1260.68325
author: James Cussens
published in: Machine Learning
publication date: 2013-04-02T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 6149410
zbMATH Keywords: inductive logic programming
zbMATH Keywords: Bayesian statistics
zbMATH Keywords: statistical relational learning
zbMATH Keywords: PRISM
zbMATH Keywords: mixture models
zbMATH Keywords: missing data
describes a project that uses: R
describes a project that uses: Mercury
describes a project that uses: BayesDA
MaRDI profile type: Publication
full work available at URL: s10994-012-5305-8
OpenAlex ID: W2092058104
cites work: Q3486661
cites work: 10.1162/jmlr.2003.3.4-5.993
cites work: Q4023085
cites work: Probabilistic Networks and Expert Systems
cites work: Parameter estimation in stochastic logic programs
cites work: Approximate Bayesian Computation for the Parameters of PRISM Programs
cites work: Q4366775
cites work: Probabilistic Inductive Querying Using ProbLog
cites work: Q4533365
cites work: Variational Bayes via propositionalized probability computation in PRISM
cites work: The execution algorithm of mercury, an efficient purely declarative logic programming language
DOI: 10.1007/S10994-012-5305-8
description: scientific article; zbMATH DE number 6149410