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» Incorporating Learning in Grid-Based Randomized SAT Solving
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AAAI
1997
13 years 6 months ago
Using CSP Look-Back Techniques to Solve Real-World SAT Instances
We report on the performance of an enhanced version of the “Davis-Putnam” (DP) proof procedure for propositional satisfiability (SAT) on large instances derived from realworld...
Roberto J. Bayardo Jr., Robert Schrag
JAIR
2008
120views more  JAIR 2008»
13 years 4 months ago
MiniMaxSAT: An Efficient Weighted Max-SAT solver
In this paper we introduce MINIMAXSAT, a new Max-SAT solver that is built on top of MINISAT+. It incorporates the best current SAT and Max-SAT techniques. It can handle hard claus...
Federico Heras, Javier Larrosa, Albert Oliveras
JAIR
2007
132views more  JAIR 2007»
13 years 4 months ago
New Inference Rules for Max-SAT
Exact Max-SAT solvers, compared with SAT solvers, apply little inference at each node of the proof tree. Commonly used SAT inference rules like unit propagation produce a simpli...
Chu Min Li, Felip Manyà, Jordi Planes
CVPR
2003
IEEE
14 years 6 months ago
Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval
The performance of image retrieval with SVM active learning is known to be poor when started with few labelled images only. In this paper, the problem is solved by incorporating t...
Lei Wang, Kap Luk Chan, Zhihua Zhang
FLAIRS
2007
13 years 7 months ago
Learning to Identify Global Bottlenecks in Constraint Satisfaction Search
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...
Diarmuid Grimes, Richard J. Wallace