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» Learning How to Propagate Using Random Probing
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AAAI
2010
13 years 5 months ago
Exploiting QBF Duality on a Circuit Representation
Search based solvers for Quantified Boolean Formulas (QBF) have adapted the SAT solver techniques of unit propagation and clause learning to prune falsifying assignments. The tech...
Alexandra Goultiaeva, Fahiem Bacchus
IJCNN
2006
IEEE
14 years 1 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
FLAIRS
2007
13 years 10 months ago
Random Subsets Support Learning a Mixture of Heuristics
Problem solvers, both human and machine, have at their disposal many heuristics that may support effective search. The efficacy of these heuristics, however, varies with the probl...
Smiljana Petrovic, Susan L. Epstein
NIPS
2008
13 years 9 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
ICML
2004
IEEE
14 years 8 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...