Output details
11 - Computer Science and Informatics
University of York
Article title
Online Bayesian inference for the parameters of PRISM programs
Type
D - Journal article
Title of journal
Machine Learning
Article number
-
Volume number
89
Issue number
3
First page of article
279
ISSN of journal
0885-6125
Year of publication
2012
Number of additional authors
0
Additional information
<24>The PRISM system is used to construct probabilistic computer programs. These probabilistic programs define arbitrarily complex probability distributions and so present a challenge to standard statistical methods for parameter estimation (whether Bayesian or non-Bayesian). This paper attacks the very difficult problem of online Bayesian analysis for PRISM programs. This requires maintaining a representation of an approximate posterior distribution which can be updated as new data arrives. The accuracy of the approximation is analysed using KL-divergence. The method is empirically tested using my own implementation of the PRISM system written in the Mercury language .
Interdisciplinary
-
Cross-referral requested
-
Research group
G - Artificial Intelligence
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
