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» Local Search Algorithms for SAT: An Empirical Evaluation
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ICDCS
2000
IEEE
14 years 28 days ago
The Effect of Nogood Learning in Distributed Constraint Satisfaction
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Makoto Yokoo, Katsutoshi Hirayama
CP
2005
Springer
14 years 2 months ago
Parallel Local Search in Comet
Abstract. The availability of commodity multiprocessors offers significant opportunities for addressing the increasing computational requirements of optimization applications. To...
Laurent Michel, Pascal Van Hentenryck
CP
2007
Springer
14 years 2 months ago
On Universal Restart Strategies for Backtracking Search
Abstract. Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that a technique called randomi...
Huayue Wu, Peter van Beek
IVC
2006
129views more  IVC 2006»
13 years 8 months ago
Measuring the performance of face localization systems
The purpose of Face localization is to determine the coordinates of a face in a given image. It is a fundamental research area in computer vision because it serves, as a necessary...
Yann Rodriguez, Fabien Cardinaux, Samy Bengio, Joh...
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis