Gibbs sampling with deterministic dependencies

Publikationstyp
Conference Paper
Publikationsdatum
2011-12-26
Sprache
English
Author
Gries, Oliver 
Institut
Softwaresysteme E-16 
TORE-URI
http://hdl.handle.net/11420/11541
First published in
Lecture notes in computer science 
Number in series
7080 LNAI
Start Page
418
End Page
427
Citation
5th international workshop, MIWAI 2011, Hyderabad, India, December 7 - 9, 2011 ; proceedings. - (Lecture Notes in Computer Science ; Vol. 7080 LNAI). - Seite 418-427 (2011)
Contribution to Conference
5th International Workshop MIWAI 2011 
Publisher DOI
10.1007/978-3-642-25725-4_37
Scopus ID
2-s2.0-84055189601
Publisher
Springer
There is a growing interest in the logical representation of both probabilistic and deterministic dependencies. While Gibbs sampling is a widely-used method for estimating probabilities, it is known to give poor results in the presence of determinism. In this paper, we consider acyclic Horn logic, a small, but significant fragment of first-order logic and show that Markov chains constructed with Gibbs sampling remain ergodic with deterministic dependencies specified in this fragment. Thus, there is a new subclass of Gibbs sampling procedures known to approximate the correct probabilities and expected to be useful for lots of applications. © 2011 Springer-Verlag.
Schlagworte
Deterministic Dependencies
Gibbs Sampling
Markov Networks
Probabilistic Inference
DDC Class
004: Informatik