Leveraging belief propagation, backtrack search, and statistics for model counting

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5015 LNCS, Issue , 2008, Pages 127-141

  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

BAYESIAN NETWORKS; BOOLEAN FUNCTIONS; MESSAGE PASSING; PARAMETER ESTIMATION; STATISTICAL METHODS;

BACKTRACK SEARCH; MINICOUNT; MODEL COUNTING;

PROBLEM SOLVING;

EID: 44649155246     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68155-7_12     Document Type: Conference Paper

References (26)

1. Bacchus, F., Dalmao, S., Pitassi, T.: Algorithms and complexity results for #SAT and Bayesian inference. In: 44nd FOCS, pp. 340-351 (October 2003)
2. Bayardo Jr., R.J., Pehoushek, J.D.: Counting models using connected components. In: 17th AAAI, Austin, TX, July 2000, pp. 157-162 (2000)
3. Darwiche, A.: New advances in compiling CNF into decomposable negation normal form. In: 16th ECAI, Valencia, Spain, August 2004, pp. 328-332 (2004)
4. Darwiche, A.: The quest for efficient probabilistic inference. In: IJCAI 2005 (July 2005) Invited Talk
5. Davis, M., Logemann, G., Loveland, D.: A machine program for theorem proving. CACM 5, 394-397 (1962)
6. Davis, M., Putnam, H.: A computing procedure for quantification theory. CACM 7, 201-215 (1960)
7. Eén, N., Sörensson, N.: MiniSat: A SAT solver with conflict-clause minimization. In: 8th SAT, St. Andrews, U.K. (June 2005)
8. Gogate, V., Dechter, R.: Approximate counting by sampling the backtrack-free search space. In: 22th AAAI, Vancouver, BC, July 2007, pp. 198-203 (2007)
9. Gomes, C.P., Hoffmann, J., Sabharwal, A., Selman, B.: From sampling to model counting. In: 20th IJCAI, Hyderabad, India, January 2007, pp. 2293-2299 (2007)
10. Gomes, C.P., Sabharwal, A., Selman, B.: Model counting: A new strategy for obtaining good bounds. In: 21th AAAI, Boston, MA, July 2006, pp. 54-61 (2006)
11. Hsu, E.I., McIlraith, S.A.: Characterizing propagation methods for boolean satisfiabilty. In: Biere, A., Gomes, C.P. (eds.) SAT 2006. LNCS, vol. 4121, pp. 325-338. Springer, Heidelberg (2006)
12. Littman, M.L., Majercik, S.M., Pitassi, T.: Stochastic Boolean satisfiability. J. Auto. Reas. 27(3), 251-296 (2001)
13. Maneva, E., Mossel, E., Wainwright, M. J.: A new look at survey propagation and its generalizations. J. Assoc. Comput. Mach. 54(4), 17 (2007)
14. Park, J.D.: MAP complexity results and approximation methods. In: 18th UAI, Edmonton, Canada, August 2002, pp. 388-396 (2002)
15. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988)
16. Pretti, M.: A message-passing algorithm with damping. J. Stat. Mech. P11008 (2005)
17. Roth, D.: On the hardness of approximate reasoning. AI J. 82(1-2), 273-302 (1996)
18. Sang, T., Bacchus, F., Beame, P., Kautz, H.A., Pitassi, T.: Combining component caching and clause learning for effective model counting. In: 7th SAT (2004)
19. Sang, T., Beame, P., Kautz, H.A.: Performing Bayesian inference by weighted model counting. In: 20th AAAI, Pittsburgh, PA, July 2005, pp. 475-482 (2005)
20. Thode, H.C.: Testing for Normality. CRC Press, Boca Raton (2002)
21. Valiant, L.G.: The complexity of computing the permanent. Theoretical Comput. Sci. 8, 189-201 (1979)
22. Wei, W., Erenrich, J., Selman, B.: Towards efficient sampling: Exploiting random walk strategies. In: 19th AAAI, San Jose, CA, July 2004, pp. 670-676 (2004)
23. Wei, W., Selman, B.: A new approach to model counting. In: Bacchus, F., Walsh, T. (eds.) SAT 2005. LNCS, vol. 3569, pp. 324-339. Springer, Heidelberg (2005)
24. Yedidia, J.S., Freeman, W.T., Weiss, Y.: Constructing free-energy approximations and generalized belief propagation algorithms. IEEE Trans. Inf. Theory 51(7), 2282-2312 (2005)
25. Yuille, A.L.: CCCP algorithms to minimize the Bethe and Kikuchi free energies: Convergent alternatives to belief prop. Neural Comput. 14(7), 1691-1722 (2002)
26. Zhou, X.-H., Sujuan, G.: Confidence intervals for the log-normal mean. Statistics In Medicine 16, 783-790 (1997)