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» A Better Algorithm for Random k-SAT
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CP
2004
Springer
14 years 1 months ago
Understanding Random SAT: Beyond the Clauses-to-Variables Ratio
It is well known that the ratio of the number of clauses to the number of variables in a random k-SAT instance is highly correlated with the instance’s empirical hardness. We con...
Eugene Nudelman, Kevin Leyton-Brown, Holger H. Hoo...
JACM
2007
79views more  JACM 2007»
13 years 7 months ago
A new look at survey propagation and its generalizations
This article provides a new conceptual perspective on survey propagation, which is an iterative algorithm recently introduced by the statistical physics community that is very effe...
Elitza N. Maneva, Elchanan Mossel, Martin J. Wainw...
IJCAI
1997
13 years 9 months ago
Hidden Gold in Random Generation of SAT Satisfiable Instances
Evaluation of incomplete algorithms that solve SAT requires to generate hard satisfiable instances. For that purpose, the kSAT uniform random generation is not usable. The other g...
Thierry Castell, Michel Cayrol
CSR
2010
Springer
14 years 17 days ago
Comparing Two Stochastic Local Search Algorithms for Constraint Satisfaction Problems
Abstract. In this survey we compare the similarities, differences and the complexities of two very different approaches to solve a general constraint satisfaction probblems (CSP). ...
Uwe Schöning
IDA
2007
Springer
14 years 1 months ago
Combining Bagging and Random Subspaces to Create Better Ensembles
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
Pance Panov, Saso Dzeroski