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Snakeinthebox codes for dimension 7
 Journal of Combinatorial Mathematics and Combinatorial Computations
, 1996
"... In the ndimensional hypercube, an nsnake is a simple path with no chords, while an ncoil is a simple cycle without chords. There has been much interest in determining the length of a maximum nsnake and a maximum ncoil. Only upper and lower bounds for these maximum lengths are known for arbitrar ..."
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Cited by 16 (0 self)
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In the ndimensional hypercube, an nsnake is a simple path with no chords, while an ncoil is a simple cycle without chords. There has been much interest in determining the length of a maximum nsnake and a maximum ncoil. Only upper and lower bounds for these maximum lengths are known
Using The Genetic Algorithm to Find SnakeInTheBox Codes
, 1994
"... Genetic Algorithms are heuristic search schemes based on a model of Darwinian evolution. Although not guaranteed to find the optimal solution, genetic algorithms have been shown to be effective at finding near optimal and, in some cases, optimal solutions to combinatorially explosive problems. Findi ..."
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Cited by 20 (3 self)
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rapidly. As a consequence, the maximum lengths of snakes have previously only been determined for n 6. Since their identification in the late 1950's, snakes (also known as SnakeInTheBox codes) have received a significant amount of research attention. SnakeInTheBox codes have a variety
ABSTRACT Using The Genetic Algorithm to Find SnakeInTheBox Codes
"... Genetic Algorithms are heuristic search schemes based on a model of Darwinian evolution. Although not guaranteed to find the optimal solution, genetic algorithms have been shown to be effective at finding near optimal and, in some cases, optimal solutions to combinatorially explosive problems. Findi ..."
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increases very rapidly. As a consequence, the maximum lengths of snakes have previously only been determined for n ≤ 6. Since their identification in the late 1950’s, snakes (also known as SnakeInTheBox codes) have received a significant amount of research attention. SnakeInTheBox codes have a variety
A Limited Memory Algorithm for Bound Constrained Optimization
 SIAM Journal on Scientific Computing
, 1994
"... An algorithm for solving large nonlinear optimization problems with simple bounds is described. ..."
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Cited by 557 (9 self)
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An algorithm for solving large nonlinear optimization problems with simple bounds is described.
Using PVM for Hunting SnakeintheBox codes
 PROCEEDINGS OF THE 1994 TRANSPUTER RESEARCH AND APPLICATIONS CONFERENCE
, 1994
"... An Incoil in Qn, the ndimensional unit cube, is a simple cycle C in Qn such that C has no chords in Qn. An Insnake is a simple (open) path S in Qn which has no chords in Qn. The problem of finding a snake of maximum length suffers from severe combinatorial explosion. This paper describes the use ..."
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Cited by 2 (0 self)
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An Incoil in Qn, the ndimensional unit cube, is a simple cycle C in Qn such that C has no chords in Qn. An Insnake is a simple (open) path S in Qn which has no chords in Qn. The problem of finding a snake of maximum length suffers from severe combinatorial explosion. This paper describes the use
An Analysis of Hypercube Space for Solving the SnakeInTheBox Problem by
"... (Under the direction of Walter D. Potter) Finding the longest snakes and coils in a hypercube is a difficult and computationally complicated problem to solve. As higher dimension hypercubes are explored, the problem quickly grows beyond the capabilities of exhaustive search techniques. Previous rese ..."
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(Under the direction of Walter D. Potter) Finding the longest snakes and coils in a hypercube is a difficult and computationally complicated problem to solve. As higher dimension hypercubes are explored, the problem quickly grows beyond the capabilities of exhaustive search techniques. Previous
Lag length selection and the construction of unit root tests with good size and power
 Econometrica
, 2001
"... It is widely known that when there are errors with a movingaverage root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We conside ..."
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Cited by 534 (14 self)
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It is widely known that when there are errors with a movingaverage root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We
UPPAAL in a Nutshell
, 1997
"... . This paper presents the overall structure, the design criteria, and the main features of the tool box Uppaal. It gives a detailed user guide which describes how to use the various tools of Uppaal version 2.02 to construct abstract models of a realtime system, to simulate its dynamical behavior, ..."
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Cited by 663 (49 self)
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, to specify and verify its safety and bounded liveness properties in terms of its model. In addition, the paper also provides a short review on casestudies where Uppaal is applied, as well as references to its theoretical foundation. 1 Introduction Uppaal is a tool box for modeling, simulation
A Scheme for RealTime Channel Establishment in WideArea Networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1990
"... Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A realtime channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A r ..."
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Cited by 710 (31 self)
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realtime service is capable of creating realtime channels on demand and guaranteeing their performance. These guarantees often take the form of lower bounds on the bandwidth allocated to a channel and upper bounds on the delays to be experienced by a packet on the channel. In this paper
Boosting a Weak Learning Algorithm By Majority
, 1995
"... We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas pr ..."
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Cited by 516 (15 self)
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presented by Schapire in his paper "The strength of weak learnability", and represents an improvement over his results. The analysis of our algorithm provides general upper bounds on the resources required for learning in Valiant's polynomial PAC learning framework, which are the best general
Results 1  10
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1,020,417