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15,419
From Typing Constraints to Typed Constraint Systems in CHR
, 2001
"... Typing constraint programs requires the flexibility of subtyping to properly express coercions between constraint domains. The typing of constraint logic programs as done in the TCLP system for example involves solving complex subtyping constraints. In this paper we present an implementation in CHR ..."
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Cited by 6 (2 self)
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Typing constraint programs requires the flexibility of subtyping to properly express coercions between constraint domains. The typing of constraint logic programs as done in the TCLP system for example involves solving complex subtyping constraints. In this paper we present an implementation in CHR
Refactoring using type constraints
 ACM Trans. Program. Lang. Syst
, 2011
"... Abstract. Type constraints express subtyperelationships between the types of program expressions that are required for typecorrectness, and were originally proposed as a convenient framework for solving type checking and type inference problems. In this paper, we show how type constraints can be ..."
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Cited by 24 (6 self)
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Abstract. Type constraints express subtyperelationships between the types of program expressions that are required for typecorrectness, and were originally proposed as a convenient framework for solving type checking and type inference problems. In this paper, we show how type constraints can
Generic Schema Matching with Cupid
 In The VLDB Journal
, 2001
"... Schema matching is a critical step in many applications, such as XML message mapping, data warehouse loading, and schema integration. In this paper, we investigate algorithms for generic schema matching, outside of any particular data model or application. We first present a taxonomy for past s ..."
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Cited by 604 (17 self)
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solutions, showing that a rich range of techniques is available. We then propose a new algorithm, Cupid, that discovers mappings between schema elements based on their names, data types, constraints, and schema structure, using a broader set of techniques than past approaches. Some of our innovations
Typing Constraint Logic Programs
 THEORY AND PRACTICE OF LOGIC PROGRAMMING
, 2001
"... We present a prescriptive type system with parametric polymorphism and subtyping for constraint logic programs. The aim of this type system is to detect programming errors statically. It introduces a type discipline for constraint logic programs and modules, while maintaining the capabilities of per ..."
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Cited by 3 (2 self)
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We present a prescriptive type system with parametric polymorphism and subtyping for constraint logic programs. The aim of this type system is to detect programming errors statically. It introduces a type discipline for constraint logic programs and modules, while maintaining the capabilities
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
 ARTIF. INTELL
, 1992
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueorderin ..."
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Cited by 457 (6 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value
Nonlinear total variation based noise removal algorithms
, 1992
"... A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using the g ..."
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Cited by 2271 (51 self)
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A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using
A Signal Processing Approach To Fair Surface Design
, 1995
"... In this paper we describe a new tool for interactive freeform fair surface design. By generalizing classical discrete Fourier analysis to twodimensional discrete surface signals  functions defined on polyhedral surfaces of arbitrary topology , we reduce the problem of surface smoothing, or fai ..."
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Cited by 654 (15 self)
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, to accommodate different types of constraints. Some constraints can be imposed without any modification of the algorithm, while others require the solution of a small associated linear system of equations. In particular, vertex location constraints, vertex normal constraints, and surface normal discontinuities
Making LargeScale Support Vector Machine Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
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Cited by 628 (1 self)
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Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large
Making LargeScale SVM Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
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Cited by 1861 (17 self)
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Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large
Mobility increases the capacity of adhoc wireless networks
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 2002
"... The capacity of adhoc wireless networks is constrained by the mutual interference of concurrent transmissions between nodes. We study a model of an adhoc network where n nodes communicate in random sourcedestination pairs. These nodes are assumed to be mobile. We examine the persession throughpu ..."
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Cited by 1220 (5 self)
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session throughput for applications with loose delay constraints, such that the topology changes over the timescale of packet delivery. Under this assumption, the peruser throughput can increase dramatically when nodes are mobile rather than fixed. This improvement can be achieved by exploiting node mobility as a
Results 1  10
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