2026-09-19T09:09:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1227582021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Martin Rinard.
Handa, Shivam.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2019-11-04T20:22:48Z
2019-11-04T20:22:48Z
2019
2019
https://hdl.handle.net/1721.1/122758
1124924206
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 139-142).
Inference metaprogramming enables effective probabilistic programming by supporting the decomposition of executions of probabilistic programs into subproblems and the deployment of hybrid probabilistic inference algorithms that apply different base probabilistic inference algorithms to different subproblems. I present the first sound and complete technique for extracting and stitching otherwise entangled subproblems for independent inference. I also prove asymptotic convergence results for hybrid inference algorithms for subproblem inference in probabilistic programs.
by Shivam Handa.
S.M.
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
142 pages ;
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Composable inference metaprogramming using subproblems
Thesis
application/pdf
2019-11-04T20:22:47Z
Publication
Master
EECS
unknown
unknown
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