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The KnuthYao QuadrangleInequality Speedup is a Consequence of TotalMonotonicity
"... There exist several general techniques in the literature for speeding up naive implementations of dynamic programming. Two of the best known are the KnuthYao quadrangle inequality speedup and the SMAWK algorithm for finding the rowminima of totally monotone matrices. Although both of these techniq ..."
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of these techniques use a quadrangle inequality and seem similar they are actually quite different and have been used differently in the literature. In this paper we show that the KnuthYao technique is actually a direct consequence of total monotonicity. As well as providing new derivations of the KnuthYao result
The KnuthYao QuadrangleInequality Speedup is a Consequence of TotalMonotonicity
"... There exist several general techniques in the literature for speeding up naive implementations of dynamic programming. Two of the best known are the KnuthYao quadrangle inequality speedup and the SMAWK algorithm for finding the rowminima of totally monotone matrices. Although both of these techni ..."
Abstract
 Add to MetaCart
of these techniques use a quadrangle inequality and seem similar they are actually quite different and have been used differently in the literature. In this paper we show that the KnuthYao technique is actually a direct consequence of total monotonicity. As well as providing new derivations of the KnuthYao result
The KnuthYao QuadrangleInequality Speedup is a Consequence of TotalMonotonicity
"... There exist several general techniques in the literature for speeding up naive implementations of dynamic programming. Two of the best known are the KnuthYao quadrangle inequality speedup and the SMAWK algorithm for finding the rowminima of totally monotone matrices. Although both of these techniq ..."
Abstract
 Add to MetaCart
of these techniques use a quadrangle inequality and seem similar they are actually quite different and have been used differently in the literature. In this paper we show that the KnuthYao technique is actually a direct consequence of total monotonicity. As well as providing new derivations of the KnuthYao result
The KnuthYao QuadrangleInequality Speedup is a Consequence of TotalMonotonicity ∗
"... There exist several general techniques in the literature for speeding up naive implementations of dynamic programming. Two of the best known are the KnuthYao quadrangle inequality speedup and the SMAWK algorithm for finding the rowminima of totally monotone matrices. Although both of these techniq ..."
Abstract
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of these techniques use a quadrangle inequality and seem similar they are actually quite different and have been used differently in the literature. In this paper we show that the KnuthYao technique is actually a direct consequence of total monotonicity. As well as providing new derivations of the KnuthYao result
Scheduling Parallel Jobs with Monotone Speedup
, 2005
"... We consider a scheduling problem where a set of jobs is apriori distributed over parallel machines. The processing time of any job is dependent on the usage of a discrete renewable resource, e.g. personnel. An amount of k units of that resource can be allocated to the jobs at any time, and the more ..."
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We consider a scheduling problem where a set of jobs is apriori distributed over parallel machines. The processing time of any job is dependent on the usage of a discrete renewable resource, e.g. personnel. An amount of k units of that resource can be allocated to the jobs at any time
On the Definition of Speedup
, 1993
"... We propose an alternative definition for the speedup of parallel algorithms. Let A be a sequential algorithm and B a parallel algorithm for solving the same problem. If A and/or B are randomized or if we are interested in their performance on a probability distribution of problem instances, the runn ..."
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Cited by 2 (0 self)
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We propose an alternative definition for the speedup of parallel algorithms. Let A be a sequential algorithm and B a parallel algorithm for solving the same problem. If A and/or B are randomized or if we are interested in their performance on a probability distribution of problem instances
Neurofuzzy modeling and control
 IEEE Proceedings
, 1995
"... Abstract  Fundamental and advanced developments in neurofuzzy synergisms for modeling and control are reviewed. The essential part of neurofuzzy synergisms comes from a common framework called adaptive networks, which uni es both neural networks and fuzzy models. The fuzzy models under the framew ..."
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Cited by 231 (1 self)
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Abstract  Fundamental and advanced developments in neurofuzzy synergisms for modeling and control are reviewed. The essential part of neurofuzzy synergisms comes from a common framework called adaptive networks, which uni es both neural networks and fuzzy models. The fuzzy models under
Online Dynamic Programming Speedups ⋆
"... Abstract. Consider the Dynamic Program h(n) = min1≤j≤n a(n, j) for n =1, 2,...,N. For arbitrary values of a(n, j), calculating all the h(n) requires Θ(N 2) time. It is well known that, if the a(n, j) satisfy the Monge property, then there are techniques to reduce the time down to O(N). This speedup ..."
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Cited by 1 (1 self)
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(N). This speedup is inherently static, i.e., it requires N to be known in advance. In this paper we show that if the a(n, j) satisfy a stronger condition, then it is possible, without knowing N in advance, to compute the values of h(n) in the order of n = 1, 2,...,N, in O(1) amortized time per h(n). This maintains
Simplifications and speedups of the Pseudoflow algorithm
 NETWORKS
, 2013
"... The pseudoflow algorithm for solving the maximum flow and minimum cut problems was devised in Hochbaum (2008). The complexity of the algorithm was shown in (2008) to be O(nm log n). Chandran and Hochbaum, (2009) demonstrated that the pseudoflow algorithm is very efficient in practice, and that the h ..."
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Cited by 3 (3 self)
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, and that the highest label version of the algorithm tends to perform best. Here, we improve the running time of the highest label pseudoflow algorithm to O(n 3) using simple data structures and to O(nm log(n 2 /m)) using the dynamic trees data structure. Both these algorithms use a new form of Depth
Diversity maximization speedup for fault localization
 In Automated Software Engineering (ASE), 2012 Proceedings of the 27th IEEE/ACM International Conference on
, 2012
"... Fault localization is useful for reducing debugging effort. However, many fault localization techniques require nontrivial number of test cases with oracles, which can determine whether a program behaves correctly for every test input. Test oracle creation is expensive because it can take much man ..."
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Cited by 5 (2 self)
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on Diversity Maximization Speedup (Dms). Dms orders a set of unlabeled test cases in a way that maximizes the effectiveness of a fault localization technique. Developers are only expected to label a much smaller number of test cases along this ordering to achieve good fault localization results. Our
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