Monolingual probabilistic programming using generalized coroutines

Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009

Volumn , Issue , 2009, Pages 285-292

  Kiselyov, Oleg ^a   Shan, Chung Chieh ^b  

^a FNMOC   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER PROGRAMMING LANGUAGES; IMPORTANCE SAMPLING; MODELING LANGUAGES; STOCHASTIC SYSTEMS;

COMBINING STRENGTH; COMPETITIVE PERFORMANCE; EXACT AND APPROXIMATE INFERENCES; GENERAL PURPOSE LANGUAGES; OPTIMIZING COMPILERS; PROBABILISTIC PROGRAMMING; PROBABILISTIC PROGRAMMING LANGUAGE; REALISTIC MODEL;

STOCHASTIC MODELS;

EID: 80053143477     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. Danvy, Olivier, and Andrzej Filinski. 1990. Abstracting control. In Lisp and functional programming, 151-160.
2. Daumé, Hal, III. 2007. Hierarchical Bayes compiler. http://www.cs.utah.edu/~hal/HBC/.
3. Dechter, Rina. 1999. Bucket elimination: A unifying framework for probabilistic inference. In Learning in graphical models, ed. Michael I. Jordan. MIT Press.
4. Domingos, Pedro, and Matthew Richardson. 2007. Markov logic: A unifying framework for statistical relational learning. In Getoor and Taskar (2007), 339-371.
5. Felleisen, Matthias, Daniel P. Friedman, Bruce F. Duba, and John Merrill. 1987. Beyond continuations. Tech. Rep. 216, Computer Science Dept., Indiana Univ.
6. Filinski, Andrzej. 1994. Representing monads. In Principles of programming languages, 446-457.
7. Fischer, Bernd, and Johann Schumann. 2003. AutoBayes: A system for generating data analysis programs from statistical models. Journal of Functional Programming 13(3):483-508. (Pubitemid 36601124)
8. Fung, Robert, and Kuo-Chu Chang. 1990. Weighing and integrating evidence for stochastic simulation in Bayesian networks. In UAI 5 (1989), 209-220.
9. Getoor, Lise, and Ben Taskar, eds. 2007. Introduction to statistical relational learning. MIT Press.
10. Goodman, Noah D., Vikash K. Mansinghka, Daniel Roy, Keith Bonawitz, and Joshua B. Tenenbaum. 2008. Church: A language for generative models. In UAI 24, 220-229.
11. Haynes, Christopher T. 1987. Logic continuations. Journal of Logic Programming 4(2):157-176.
12. Jaeger, Manfred, Petr Lidman, and Juan L. Mateo. 2007. Comparative evaluation of probabilistic logic languages and systems. In Proceedings of mining and learning with graphs. http://www.cs.aau.dk/~jaeger/plsystems/.
13. Kiselyov, Oleg. 2006. Native delimited continuations in (bytecode) OCaml. http://okmij.org/ftp/Computation/Continuations.html#caml-shift.
14. Koller, Daphne, David McAllester, and Avi Pfeffer. 1997. Effective Bayesian inference for stochastic programs. In AAAI, 740-747.
15. Leroy, Xavier, Damien Doligez, Jacques Garrigue, Didier Rémy, and Jérôme Vouillon. 2008. The Objective Caml system, release 3.11. INRIA.
16. McAllester, David, Michael Collins, and Fernando Pereira. 2008. Case-factor diagrams for structured probabilistic modeling. Journal of Computer and System Sciences 74(1):84-96. (Pubitemid 47625407)
17. Milch, Brian, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov. 2007. BLOG: Probabilistic models with unknown objects. In Getoor and Taskar (2007), 373-398.
18. Minka, Tom, John M. Winn, John P. Guiver, and Anitha Kannan. 2009. Infer.NET 2.2. Microsoft Research. http://research.microsoft.com/infernet.
19. Murphy, Kevin. 2007a. Bayes Net Toolbox for Matlab. http: //www.cs.ubc.ca/~murphyk/Software/BNT/bnt.html.
20. Murphy, Kevin. 2007b. Software for graphical models: A review. International Society for Bayesian Analysis Bulletin 14(4):13-15.
21. Pfeffer, Avi. 2007a. The design and implementation of IBAL: A general-purpose probabilistic language. In Getoor and Taskar (2007), 399-432.
22. Pfeffer, Avi. 2007b. A general importance sampling algorithm for probabilistic programs. Tech. Rep. TR-12-07, Harvard Univ. Poole, David, and Alan Mackworth. 2009. Artificial intelligence: Foundations of computational agents. Cambridge Univ. Press.
23. Radul, Alexey. 2007. Report on the probabilistic language Scheme. In DLS '07: Proceedings of the 2007 symposium on dynamic languages, 2-10. New York: ACM Press. (Pubitemid 351429525)
24. Russell, Stuart, and Peter Norvig. 2003. Artificial intelligence: A modern approach. 2nd ed. Prentice-Hall.
25. Sato, Taisuke. 2008. A glimpse of symbolic-statistical modeling by PRISM. Journal of Intelligent Information Systems 31(2): 161-176.
26. Shachter, Ross D., and Mark A. Peot. 1990. Simulation approaches to general probabilistic inference on belief networks. In UAI 5 (1989), 221-234.