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Properties of the LogBarrier Function on Degenerate Nonlinear Programs
 MATH. OPER. RES
, 1999
"... We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondordersufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily linearly independ ..."
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Cited by 13 (0 self)
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We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondordersufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily linearly
Properties of the LogBarrier Function on Degenerate Nonlinear Programs
, 2001
"... Abstract. We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondorder sufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily linearl ..."
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Abstract. We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondorder sufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily
Properties of the LogBarrier Function on Degenerate Nonlinear Programs
, 2002
"... Abstract. We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondorder sufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily linear ..."
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Abstract. We examine the sequence of local minimizers of the logbarrier function for a nonlinear program near a solution at which secondorder sufficient conditions and the MangasarianFromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily
The synchronous dataflow programming language LUSTRE
 Proceedings of the IEEE
, 1991
"... This paper describes the language Lustre, which is a dataflow synchronous language, designed for programming reactive systems  such as automatic control and monitoring systems  as well as for describing hardware. The dataflow aspect of Lustre makes it very close to usual description tools in t ..."
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Cited by 647 (53 self)
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formalism is very similar to temporal logics. This allows the language to be used for both writing programs and expressing program properties, which results in an original program verification methodology. 1 Introduction Reactive systems Reactive systems have been defined as computing systems which
The Semantics Of Constraint Logic Programs
 JOURNAL OF LOGIC PROGRAMMING
, 1996
"... This paper presents for the first time the semantic foundations of CLP in a selfcontained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and comp ..."
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Cited by 872 (14 self)
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This paper presents for the first time the semantic foundations of CLP in a selfcontained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and complete proofs for the main lemmas. Importantly, we clarify which theorems depend on conditions such as solution compactness, satisfaction completeness and independence of constraints. Second, we generalize the original results to allow for incompleteness of the constraint solver. This is important since almost all CLP systems use an incomplete solver. Third, we give conditions on the (possibly incomplete) solver which ensure that the operational semantics is confluent, that is, has independence of literal scheduling.
Learning the Kernel Matrix with SemiDefinite Programming
, 2002
"... Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information ..."
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Cited by 780 (22 self)
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problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied
Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
 SIAM Journal on Optimization
, 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
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Cited by 557 (12 self)
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We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized
The SPLASH2 programs: Characterization and methodological considerations
 INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE
, 1995
"... The SPLASH2 suite of parallel applications has recently been released to facilitate the study of centralized and distributed sharedaddressspace multiprocessors. In this context, this paper has two goals. One is to quantitatively characterize the SPLASH2 programs in terms of fundamental propertie ..."
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Cited by 1399 (12 self)
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The SPLASH2 suite of parallel applications has recently been released to facilitate the study of centralized and distributed sharedaddressspace multiprocessors. In this context, this paper has two goals. One is to quantitatively characterize the SPLASH2 programs in terms of fundamental
SNOPT: An SQP Algorithm For LargeScale Constrained Optimization
, 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
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Cited by 582 (23 self)
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Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first
Constraint Logic Programming: A Survey
"... Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve in differe ..."
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Cited by 864 (25 self)
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Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve
Results 1  10
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