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» Constraint Solving for Interpolation
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116
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CP
2001
Springer
15 years 5 months ago
Solving Non-binary CSPs Using the Hidden Variable Encoding
Non-binary constraint satisfaction problems (CSPs) can be solved in two different ways. We can either translate the problem into an equivalent binary one and solve it using well-e...
Nikos Mamoulis, Kostas Stergiou
98
Voted
ICML
2008
IEEE
16 years 1 months ago
Efficiently solving convex relaxations for MAP estimation
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
M. Pawan Kumar, Philip H. S. Torr
101
Voted
CSCLP
2006
Springer
15 years 4 months ago
Bipolar Preference Problems: Framework, Properties and Solving Techniques
Real-life problems present several kinds of preferences. We focus on problems with both positive and negative preferences, that we call bipolar preference problems. Although seemin...
Stefano Bistarelli, Maria Silvia Pini, Francesca R...
91
Voted
AAAI
2007
15 years 3 months ago
Using Expectation Maximization to Find Likely Assignments for Solving CSP's
We present a new probabilistic framework for finding likely variable assignments in difficult constraint satisfaction problems. Finding such assignments is key to efficient sea...
Eric I. Hsu, Matthew Kitching, Fahiem Bacchus, She...
JFP
2008
97views more  JFP 2008»
14 years 11 months ago
HM(X) type inference is CLP(X) solving
The HM(X) system is a generalization of the Hindley/Milner system parameterized in the constraint domain X. Type inference is performed by generating constraints out of the progra...
Martin Sulzmann, Peter J. Stuckey