This paper demonstrates the generation of a linear-time query-answering algorithm based on the constructive proof of Higman's lemma by Murthy and Russell [Proceedings of the 5th IEEE Symposium on Logic in Computer...
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This paper demonstrates the generation of a linear-time query-answering algorithm based on the constructive proof of Higman's lemma by Murthy and Russell [Proceedings of the 5th IEEE Symposium on Logic in Computer Science, 1990, p. 257-267]. The target problem is linear-time evaluation of a fixed disjunctive monadic query on an indefinite database over linearly ordered domains, first posed by van der Meyden [Proceedings of the 11th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1992, p. 331-345]. Van der Meyden showed the existence of a linear-time algorithm, but an explicit construction has, until now, not been reported. (C) 2003 Elsevier Science (USA). All rights reserved.
This paper demonstrates the generation of a linear-time query-answering algorithm based on the constructive proof of Higman's lemma by Murthy and Russell [Proceedings of the 5th IEEE Symposium on Logic in Computer...
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This paper demonstrates the generation of a linear-time query-answering algorithm based on the constructive proof of Higman's lemma by Murthy and Russell [Proceedings of the 5th IEEE Symposium on Logic in Computer Science, 1990, p. 257-267]. The target problem is linear-time evaluation of a fixed disjunctive monadic query on an indefinite database over linearly ordered domains, first posed by van der Meyden [Proceedings of the 11th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1992, p. 331-345]. Van der Meyden showed the existence of a linear-time algorithm, but an explicit construction has, until now, not been reported. (C) 2003 Elsevier Science (USA). All rights reserved.
This paper deals with optimization of functions that depend on (large-scale) data via a linear transformation of rank two. An algorithm is presented which-under mild assumptions-finds the global solution with polynomi...
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This paper deals with optimization of functions that depend on (large-scale) data via a linear transformation of rank two. An algorithm is presented which-under mild assumptions-finds the global solution with polynomial-time complexity in the worst case, provided the critical points of the objective can be controlled with the same effort. Moreover, for important subclasses of objectives including the linear-fractional, and the quadratic case, we arrive at a linear-time algorithm. For both cases, small simulation studies are provided to illustrate the average case runtime behaviour. As a possible application, sensitivity of cost assessment in communication networks is addressed where the problems may have tens of thousands of variables. (C) 2003 Elsevier B.V. All rights reserved.
A linear-time algorithm for filling regions defined by closed contours in raster format is proposed. The algorithm relies on a single pass contour labeling and the actual filling is done in a scan-line manner, visitin...
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A linear-time algorithm for filling regions defined by closed contours in raster format is proposed. The algorithm relies on a single pass contour labeling and the actual filling is done in a scan-line manner, visiting the interior pixels only once. The interior endpoints of the scan-lines are discovered solely on the basis of the labeled contour. Despite its simplicity and low computation cost, the proposed method fills-in arbitrary shapes correctly, with no obvious exceptions. Possible special cases may arise from the 8-connectivity, inner contour detection. However, in extensive tests on complicated images, the proposed labeling scheme has given correct results. (c) 2005 Elsevier Ltd. All rights reserved.
A new linear-time algorithm is presented in this paper that simultaneously, labels connected components (to be referred to merely as components in this paper) and their contours in binary images. The main step of this...
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A new linear-time algorithm is presented in this paper that simultaneously, labels connected components (to be referred to merely as components in this paper) and their contours in binary images. The main step of this algorithm is to use a contour tracing technique to detect the external contour and possible internal contours of each component, and also to identify and label the interior area of each component. Labeling is done in a single pass over the image, while contour points are revisited more than once, but no more than a constant number of times. Moreover, no re-labeling is required throughout the entire process, as it is required by other algorithms. Experimentation on various types of images (characters, halftone pictures, photographs, newspaper, etc.) shows that our method outperforms methods that use the equivalence technique. Our algorithm not only labels components but also extracts component contours and sequential orders of contour points, which can be useful for many applications. (C) 2003 Elsevier Inc. All rights reserved.
The computational complexity of learning from binary examples is investigated for linear threshold neurons. We introduce combinatorial measures that create classes of infinitely many learning problems with sample rest...
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The computational complexity of learning from binary examples is investigated for linear threshold neurons. We introduce combinatorial measures that create classes of infinitely many learning problems with sample restrictions. We analyze how the complexity of these problems depends on the values for the measures. The results are established as dichotomy theorems showing that each problem is either NP-complete or solvable in polynomial time. In particular, we consider consistency and maximum consistency problems for neurons with binary weights, and maximum consistency problems for neurons with arbitrary weights. We determine for each problem class the dividing line between the NP-complete and polynomial-time solvable problems. Moreover, all efficiently solvable problems are shown to have constructive algorithms that require no more than lineartime on a random access machine model. Similar dichotomies are exhibited for neurons with bounded threshold. The results demonstrate on the one hand that the consideration of sample constraints can lead to the discovery of new efficient algorithms for non-trivial learning problems. On the other hand, hard learning problems may remain intractable even for severely restricted samples.
The obnoxious center problem in a graph G asks for a location on an edge of the graph such that the minimum weighted distance from this point to a vertex of the graph is as large as possible. An algorithm is given whi...
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The obnoxious center problem in a graph G asks for a location on an edge of the graph such that the minimum weighted distance from this point to a vertex of the graph is as large as possible. An algorithm is given which finds the obnoxious center on a weighted cactus graph in O(cn) time, where n is the number of vertices and c is the number of different vertex weights (called marks). (C) 2003 Published by Elsevier B.V.
The obnoxious center problem in a graph G asks for a location on an edge of the graph such that the minimum weighted distance from this point to a vertex of the graph is as large as possible. An algorithm is given whi...
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The obnoxious center problem in a graph G asks for a location on an edge of the graph such that the minimum weighted distance from this point to a vertex of the graph is as large as possible. An algorithm is given which finds the obnoxious center on a weighted cactus graph in O(cn) time, where n is the number of vertices and c is the number of different vertex weights (called marks). (C) 2003 Published by Elsevier B.V.
Suffix trees are the fundamental data structure of combinatorial pattern matching on words. Suffix trees have been used in order to give optimal solutions to a great variety of problems oil static words, but for pract...
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Suffix trees are the fundamental data structure of combinatorial pattern matching on words. Suffix trees have been used in order to give optimal solutions to a great variety of problems oil static words, but for practical situations, such as in a text editor, where the incremental changes of the text make dynamic updating of the corresponding suffix trees necessary, this data structure alone has not been used with success. We prove that, for dynamic modifications of order 0 (1) of words of length it, any suffix tree updating algorithm. such as the ones proposed by McCreight, requires 0(n) worst-case running time, as for the full reconstruction of the suffix tree. Consequently, we argue that this data Structure alone is not appropriate for the solution of combinatorial problems on words that change dynamically.
We prove that every (claw, net)-free graph contains an induced doubly dominating cycle or a dominating pair. Moreover, using LexBFS we present a lineartimealgorithm which, for a given (claw, net)-free graph, finds e...
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We prove that every (claw, net)-free graph contains an induced doubly dominating cycle or a dominating pair. Moreover, using LexBFS we present a lineartimealgorithm which, for a given (claw, net)-free graph, finds either a dominating pair or an induced doubly dominating cycle. We show also how one can use structural properties of (claw, net)-free graphs to solve efficiently the domination, independent domination, and independent set problems on these graphs. (C) 2003 Elsevier B.V. All rights reserved.
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