Survey propagation revisited

Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence, UAI 2007

Volumn , Issue , 2007, Pages 217-226

  Kroc, Lukas ^a   Sabharwal, Ashish ^a   Selman, Bart ^a  

^a Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BELIEF PROPAGATION; COMBINATORIAL PROBLEM; MARGINAL PROBABILITY; MARGINALS; NON-TRIVIAL; RANDOM FORMULAS; SATISFIABILITY OF BOOLEAN FORMULAS; SURVEY PROPAGATION;

ARTIFICIAL INTELLIGENCE; EXPERIMENTS; SURVEYS;

BOOLEAN ALGEBRA;

EID: 80053197475     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. D. Achlioptas and F. Ricci-Tersenghi. On the solution-space geometry of random constraint satisfaction problems. In 38th STOC, pages 130-139, Seattle, WA, 2006. (Pubitemid 44306546)
2. A. Braunstein and R. Zecchina. Survey propagation as local equilibrium equations. J. Stat. Mech., P06007, 2004. URL http://lanl.arXiv.org/cond-mat/ 0312483.
3. A. Braunstein, M. Mezard, and R. Zecchina. Survey propagation: an algorithm for satisfiability. Random Structures and Algorithms, 27:201, 2005.
4. F. R. Kschischang, B. J. Frey, and H. A. Loeliger. Factor graphs and the sum-product algorithm. Information Theory, IEEE Transactions on, 47(2):498-519, 2001. (Pubitemid 32318087)
5. E. N. Maneva, E. Mossel, and M. J. Wainwright. A new look at survey propagation and its generalizations. In 16th SODA, pages 1089-1098, Vancouver, Canada, 2005. (Pubitemid 40851477)
6. M. Mezard, G. Parisi, and R. Zecchina. Analytic and Algorithmic Solution of Random Satisfiability Problems. Science, 297(5582):812-815, 2002. doi: 10.1126/science. 1073287. (Pubitemid 34839626)
7. E. Mossel. Personal communication, April 2007.
8. K. Murphy, Y. Weiss, and M. Jordan. Loopy belief propagation for approximate inference: An empirical study. In 15th UAI, pages 467-475, Sweden, July 1999.
9. R. E. Neapolitan. Learning Bayesian Networks. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 2004. ISBN 0130125342.
10. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kauf., 1988.
11. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2005. URL http://www.R-project.org. ISBN 3-900051-07-0.
12. W. Wei, J. Erenrich, and B. Selman. Towards efficient sampling: Exploiting random walk strategies. In 19th AAAI, pages 670-676, San Jose, CA, July 2004.