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558,087
A memetic approach to golomb rulers
 Parallel Problem Solving From Nature IX
, 2006
"... Abstract. Finding Golomb rulers is an extremely challenging optimization problem with many practical applications. This problem has been approached by a variety of search methods in recent years. We consider in this work a hybrid evolutionary algorithm that incorporates ideas from greedy randomized ..."
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significantly outperforms earlier approaches (including other hybrid EAs, as well as hybridizations of local search and constraint programming), finding optimal rulers where the mentioned techniques failed. 1
A Lagrangian Relaxation for Golomb Rulers
"... Abstract. The Golomb Ruler Problem asks to position n integer marks on a ruler such that all pairwise distances between the marks are distinct and the ruler has minimum total length. It is a very challenging combinatorial problem, and provably optimal rulers are only known for n up to 26. Lower boun ..."
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Abstract. The Golomb Ruler Problem asks to position n integer marks on a ruler such that all pairwise distances between the marks are distinct and the ruler has minimum total length. It is a very challenging combinatorial problem, and provably optimal rulers are only known for n up to 26. Lower
Maximizing Irregularity and the Golomb Ruler Problem
, 1997
"... The problem of attempting to construct radar signals whose ambiguity functions are sharply peaked in both time and frequency gives rise to a quantitative concept of the irregularity of a distribution of points. The problem of maximizing the irregularity of N points distributed on a bounded closed in ..."
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the (continuous) irregularity function become questions about this integral construction, many of which can be answered easily and elegantly. One important question about the integral construction has been previously studied under the name of the Golomb Ruler Problem. It turns out that maximizing irregularity
Locally weighted learning
 ARTIFICIAL INTELLIGENCE REVIEW
, 1997
"... This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, ass ..."
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Cited by 594 (53 self)
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This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias
Constraint Networks
, 1992
"... Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expression ..."
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Cited by 1149 (43 self)
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Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint
A PERFORMANCE EVALUATION OF LOCAL DESCRIPTORS
, 2005
"... In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the HarrisAffine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how their perfo ..."
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Cited by 1752 (53 self)
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In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the HarrisAffine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how
The FF planning system: Fast plan generation through heuristic search
 Journal of Artificial Intelligence Research
, 2001
"... We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be ind ..."
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Cited by 822 (53 self)
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We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts
Modelling the Golomb Ruler Problem
, 1999
"... . The Golomb ruler problem has been proposed as a challenging constraint satisfaction problem. We consider a large number of different models of this problem, both binary and nonbinary. The problem can be modelled using quaternary constraints, but in practice using a set of auxiliary variables and ..."
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Cited by 33 (9 self)
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. The Golomb ruler problem has been proposed as a challenging constraint satisfaction problem. We consider a large number of different models of this problem, both binary and nonbinary. The problem can be modelled using quaternary constraints, but in practice using a set of auxiliary variables
Linguistic Complexity: Locality of Syntactic Dependencies
 COGNITION
, 1998
"... This paper proposes a new theory of the relationship between the sentence processing mechanism and the available computational resources. This theory  the Syntactic Prediction Locality Theory (SPLT)  has two components: an integration cost component and a component for the memory cost associa ..."
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Cited by 486 (31 self)
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This paper proposes a new theory of the relationship between the sentence processing mechanism and the available computational resources. This theory  the Syntactic Prediction Locality Theory (SPLT)  has two components: an integration cost component and a component for the memory cost
Local SearchBased Hybrid Algorithms for Finding Golomb Rulers
"... Abstract. The Golomb Ruler Problem is a very hard combinatorial optimization problem that has been tackled with many different approaches, such as Constraint Programming (CP), Local Search (LS), Evolutionary Algorithms (EAs), and hybrid LS and CP, among others. This paper describes several local sea ..."
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Cited by 6 (0 self)
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Abstract. The Golomb Ruler Problem is a very hard combinatorial optimization problem that has been tackled with many different approaches, such as Constraint Programming (CP), Local Search (LS), Evolutionary Algorithms (EAs), and hybrid LS and CP, among others. This paper describes several local
Results 1  10
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