Reduced traces and JITing in Church

Church is a Turing-complete probabilistic programming language, designed for inference. By allowing for easy description and manipulation of distributions, it allows one to describe classical Al models in compact ways, providing a language for very rich expression. However, for inference in Bayes nets, Hidden Markov Models, and topic models, the very settings for which probabilistic programming languages like Church were designed for, researchers typically instead write special cased algorithms in regular programming languages to maximize performance. In this paper, we argue that an extremely general language can still support very fast inference. We first introduce the theoretical aspects of our Church-like language, including many implementation tradeoffs. While the language is extremely hands-off and easy to use, we also allow for more detailed specification of the inference. Lastly, we demonstrate empirical results displaying our progress towards general languages which can perform inference quickly, and point out many future directions for research.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Wu, Jeff (Jeffrey K.)

Advisor dc:contributor.advisor

• Josh Tenenbaum.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/85526

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/85526