graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze such data, a signal processing theory f...
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ISBN:
(纸本)9781424442959
graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze such data, a signal processing theory for evaluating these techniques akin to detection and estimation in the classical Euclidean setting remains to be developed. In this paper we show the conceptual advantages gained by formulating graph analysis problems in a signal processing framework by way of a practical example: detection of a subgraph embedded in a background graph. We describe an approach based on detection theory and provide empirical results indicating that the test statistic proposed has reasonable power to detect dense subgraphs in large random graphs.
In this paper, we investigate quantum algorithms for graph colouring problems, in particular for 2- and 3-colouring of graphs. Our main goal is to establish a set of quantum representations and operations suitable for...
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In this paper, we investigate quantum algorithms for graph colouring problems, in particular for 2- and 3-colouring of graphs. Our main goal is to establish a set of quantum representations and operations suitable for the problem at hand. We propose unitaryas well as measurement-based quantum computations, also taking inspiration from answer set programming, a form of declarative programming close to traditional logic programming. The approach used is one in which we first generate arbitrary solutions to the problem, then constraining these according to the problem's input. Though we do not achieve fundamental speed-ups, our algorithms show how quantum concepts can be used for programming and moreover exhibit structural differences. For example, we compute all possible colourings at the same time. We compare our algorithms with classical ones, highlighting how the same type of difficulties give rise to NP-complete behaviour, and propose possible improvements. (C) 2008 Elsevier B.V. All rights reserved.
This article reports the results of an extensive experimental analysis of efficient algorithms for computing graph spanners in the data streaming model, where an (alpha, beta)-spanner of a graph G is a subgraph S subs...
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This article reports the results of an extensive experimental analysis of efficient algorithms for computing graph spanners in the data streaming model, where an (alpha, beta)-spanner of a graph G is a subgraph S subset of G such that for each pair of vertices the distance in S is at most a times the distance in G plus beta. To the best of our knowledge, this is the first computational study of graph spanner algorithms in a streaming setting. We compare experimentally the randomized algorithms proposed by Baswana (http://***/abstract?id=oai:***:cs/0611023) and by Elkin (In: Proceedings of the 34th International Colloquium on Automata, Languages and Programming (ICALP 2007), Wroclaw, Poland, pp. 716-727, 9-13 July 2007) for general stretch factors with the deterministic algorithm presented by Ausiello et al. (In: Proceedings of the 15th Annual European Symposium on algorithms (ESA 2007), Engineering and Applications Track, Eilat, Israel, 8-10 October 2007. LNCS, vol. 4698, pp. 605-617, 2007), designed for building small stretch spanners. All the algorithms we implemented work in a data streaming model where the input graph is given as a stream of edges in arbitrary order, and all of them need a single pass over the data. Differently from the algorithm in Ausiello et al., the algorithms in Baswana (http://***/abstract?id=oai:***:cs/0611023) and Elkin (In: Proceedings of the 34th International Colloquium on Automata, Languages and Programming (ICALP 2007), Wroclaw, Poland, pp. 716-727, 9-13 July 2007) need to know in advance the number of vertices in the graph. The results of our experimental investigation on several input families confirm that all these algorithms are very efficient in practice, finding spanners with stretch and size much smaller than the theoretical bounds and comparable to those obtainable by off-line algorithms. Moreover, our experimental findings confirm that small values of the stretch factor are the case of
We prove a relationship between the CLEANING problem and the BALANCED VERTEX-ORDERING problem, namely that the minimum total imbalance of a graph equals twice the brush number of a graph. This equality has consequence...
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We prove a relationship between the CLEANING problem and the BALANCED VERTEX-ORDERING problem, namely that the minimum total imbalance of a graph equals twice the brush number of a graph. This equality has consequences for both problems. On one hand, it allows us to prove the A(P-completeness of the CLEANING problem, which was conjectured by Messinger et al. [M.-E. Messinger, R.J. Nowakowski, P. Pralat, Cleaning a network with brushes, Theoret. Comput. Sci. 399 (2008) 191-205]. On the other hand, it also enables us to design a faster algorithm for the BALANCED VERTEX-ORDERING problem [J. Kara, K. Kratochvil, D. Wood, On the complexity of the balanced vertex ordering problem, Discrete Math. Theor. Comput. Sci. 9 (1) (2007) 193-202]. (C) 2009 Elsevier B.V. All rights reserved.
Suppose that we are given a directed graph D = (V, A) with specified vertices r(1), r(2) is an element of V. this paper, we consider the problem of discerning the existence of a pair of arc-disjoint spanning in-arbore...
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Suppose that we are given a directed graph D = (V, A) with specified vertices r(1), r(2) is an element of V. this paper, we consider the problem of discerning the existence of a pair of arc-disjoint spanning in-arborescence rooted at r(1) and out-arborescence rooted at r(2), and finding such arborescences if they exist. It is known (Bang-Jensen (1991) [1]) that this problem is NP-complete even if r(1) = r(2). As a special case, it is only known (Bang-Jensen (1991) [1]) that this problem in a tournament can be solved in polynomial time. In this paper, we give a linear-time algorithm for this problem in a directed acyclic graph. We also consider an extension of our problem to the case where we have multiple roots for in-arborescences and out-arborescences, respectively. (C) 2009 Elsevier B.V. All rights reserved.
Results on graph turnpike problem without distinctness, including its NP-completeness, and an O(m+n log n) algorithm, is presented. The usual turnpike problem has all pairwise distances given, but does not specify whi...
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Results on graph turnpike problem without distinctness, including its NP-completeness, and an O(m+n log n) algorithm, is presented. The usual turnpike problem has all pairwise distances given, but does not specify which pair of vertices we corresponds to. There are two other problems that can be viewed as special cases of the graph turnpike problem, including the bandwidth problem and the low-distortion graph embedding problem. The aim for the turnpike problem in the NP-complete is to orient the edges with weights wi in either direction so that when the whole cycle is transversed in the real line, it returns to a chosen starting point for the cycle. An instance of the turnpike problem with or without distinctness is uniquely mappable if there exists at most one solution up to translation and choice of orientation.
We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph matching problem as a least-squa...
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We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices. The concave relaxation has the same global minimum as the initial graph matching problem, but the search for its global minimum is also a hard combinatorial problem. We, therefore, construct an approximation of the concave problem solution by following a solution path of a convex-concave problem obtained by linear interpolation of the convex and concave formulations, starting from the convex relaxation. This method allows to easily integrate the information on graph label similarities into the optimization problem, and therefore, perform labeled weighted graph matching. The algorithm is compared with some of the best performing graph matching methods on four data sets: simulated graphs, QAPLib, retina vessel images, and handwritten Chinese characters. In all cases, the results are competitive with the state of the art.
We explore three important avenues of research in algorithmic graph-minor theory, which all stem from a key min-max relation between the treewidth of a graph and its largest grid minor. This min-max relation is a keys...
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We explore three important avenues of research in algorithmic graph-minor theory, which all stem from a key min-max relation between the treewidth of a graph and its largest grid minor. This min-max relation is a keystone of the graph Minor Theory of Robertson and Seymour, which ultimately proves Wagner's Conjecture about the structure of minor-closed graph properties. First, we obtain the only known polynomial min-max relation for graphs that do not exclude any fixed minor, namely, map graphs and power graphs. Second, we obtain explicit (and improved) bounds on the min-max relation for an important class of graphs excluding a minor, namely, K3, k-minor-free graphs, using new techniques that do not rely on graph Minor Theory. These two avenues lead to faster fixed-parameter algorithms for two families of graph problems, called minor-bidimensional and contraction-bidimensional parameters, which include feedback vertex set, vertex cover, minimum maximal matching, face cover, a series of vertex-removal parameters, dominating set, edge dominating set, R-dominating set, connected dominating set, connected edge dominating set, connected R-dominating set, and unweighted TSP tour. Third, we disprove a variation of Wagner's Conjecture for the case of graph contractions in general graphs, and in a sense characterize which graphs satisfy the variation. This result demonstrates the limitations of a general theory of algorithms for the family of contraction-closed problems (which includes, for example, the celebrated dominating-set problem). If this conjecture had been true, we would have had an extremely powerful tool for proving the existence of efficient algorithms for any contraction-closed problem, like we do for minor-closed problems via graph Minor Theory.
We explore three important avenues of research in algorithmic graph-minor theory, which all stem from a key min-max relation between the treewidth of a graph and its largest grid minor. This min-max relation is a keys...
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ISBN:
(纸本)3540496947
We explore three important avenues of research in algorithmic graph-minor theory, which all stem from a key min-max relation between the treewidth of a graph and its largest grid minor. This min-max relation is a keystone of the graph Minor Theory of Robertson and Seymour, which ultimately proves Wagner's Conjecture about the structure of minor-closed graph properties. First, we obtain the only known polynomial min-max relation for graphs that do not exclude any fixed minor, namely, map graphs and power graphs. Second, we obtain explicit (and improved) bounds on the min-max relation for an important class of graphs excluding a minor, namely, K3, k-minor-free graphs, using new techniques that do not rely on graph Minor Theory. These two avenues lead to faster fixed-parameter algorithms for two families of graph problems, called minor-bidimensional and contraction-bidimensional parameters, which include feedback vertex set, vertex cover, minimum maximal matching, face cover, a series of vertex-removal parameters, dominating set, edge dominating set, R-dominating set, connected dominating set, connected edge dominating set, connected R-dominating set, and unweighted TSP tour. Third, we disprove a variation of Wagner's Conjecture for the case of graph contractions in general graphs, and in a sense characterize which graphs satisfy the variation. This result demonstrates the limitations of a general theory of algorithms for the family of contraction-closed problems (which includes, for example, the celebrated dominating-set problem). If this conjecture had been true, we would have had an extremely powerful tool for proving the existence of efficient algorithms for any contraction-closed problem, like we do for minor-closed problems via graph Minor Theory.
A method to relabel noisy multi-criteria data sets is presented, taking advantage of the transitivity of the non-monotonicity relation to formulate the problem as an efficiently solvable maximum independent set proble...
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A method to relabel noisy multi-criteria data sets is presented, taking advantage of the transitivity of the non-monotonicity relation to formulate the problem as an efficiently solvable maximum independent set problem. A framework and an algorithm for general loss functions are presented. and the flexibility of the approach is indicated by some examples, showcasing the ease with which the method can handle application-specific loss functions. Both didactical examples and real-life applications are provided, using the zero-one, the L1 and the squared loss functions, as well as combinations thereof. (C) 2009 Elsevier Inc. All rights reserved.
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