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Constraint satisfaction: the approximability of minimization problems

Proceedings of Computational Complexity. Twelfth Annual IEEE Conference, 2002
This paper continues the work initiated by N. Creignou (1995) and S. Khanna et al. (1997) who classify maximization problems derived from Boolean constraint satisfaction. We study the approximability of minimization problems derived thence. A problem in this framework is characterized by a collection F of "constraints" (i.e., functions f: {0,1}/sup k ...
Sanjeev Khanna   +2 more
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Fast approximate denial constraint discovery

Proceedings of the VLDB Endowment, 2022
We investigate the problem of discovering approximate denial constraints (DCs), for finding DCs that hold with some exceptions to avoid overfitting real-life dirty data and facilitate data cleaning tasks. Different methods have been proposed to address the problem, by following the same framework consisting of two phases. In the first phase a structure
Renjie Xiao   +3 more
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Approximating Data in Constraint Databases

2000
Approximate representation of any spatio-temporal variable, by some interpolation function, is necessary when it is measured only sporadically. This paper argues that the approximate representation can be captured by a constraint database. Since constraint databases can be queried via standard query languages - such as relational algebra, SQL and ...
Rui Chen, Min Ouyang, Peter Z. Revesz
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Complex approximation with additional constraints

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
A powerful signal exchange algorithm for the solution of the complex Chebyshev approximation problem was introduced by P.T.P. Tang (1988). It was picked up and modified by A. Alkhairy et al. (1991) for the design of digital FIR filters. This algorithm is extended to solve the approximation problem in conjunction with additional constraints, such as ...
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Dynamic approximation of complex graphical constraints by linear constraints

Proceedings of the 15th annual ACM symposium on User interface software and technology, 2002
Current constraint solving techniques for interactive graphical applications cannot satisfactorily handle constraints such as non-overlap, or containment within non-convex shapes or shapes with smooth edges. We present a generic new technique for efficiently handling such kinds of constraints based on trust regions and linear arithmetic constraint ...
Nathan Hurst   +2 more
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Complexity of Approximating CSP with Balance / Hard Constraints

Theory of Computing Systems, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Venkatesan Guruswami, Euiwoong Lee
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Constraint database query evaluation with approximation

Proceedings International Conference on Information Technology: Coding and Computing, 2002
Considers the problem of solving a large number of simple systems of linear constraints. This problem occurs in the context of constraint databases. The developed methodology is based on a hierarchical evaluation of the constraints, which are first simplified and replaced by approximations.
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Approximated Consistency for Knapsack Constraints

2003
While global constraints give a broader view on the entire problem and therefore allow more effective constraint propagation, the development of efficient generalized arc-consistency (GAC) algorithms for global constraints is frequently prevented by the fact that the associated decision problems are NP-hard. A prominent example for this is the Knapsack
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On approximate constraint satisfaction

Russian Mathematics, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Soft Constraint of Equality: Complexity and Approximability

2008
We introduce the SoftAllEqual global constraint, which maximizes the number of equalities holding between pairs of assignments to a set of variables. We study the computational complexity of propagating this constraint, showing that it is intractable in general, since maximizing the number of pairs of equally assigned variables in a set is NP-hard. We
Emmanuel Hebrard   +2 more
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