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The Grötzsch Theorem for the hypergraph of maximal cliques
 Electron. J. Combin
, 1999
"... In this paper, we extend the Grotzsch Theorem by proving that the clique hypergraph of every planar graph is 3colorable. We also extend this result to list colorings by proving that for every planar or projective planar graph G. Finally, 4choosability is established for the class of loc ..."
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Cited by 10 (0 self)
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In this paper, we extend the Grotzsch Theorem by proving that the clique hypergraph of every planar graph is 3colorable. We also extend this result to list colorings by proving that for every planar or projective planar graph G. Finally, 4choosability is established for the class
1 EMBEDDED MAXIMAL CLIQUES AND INCOMPLETENESS by
, 2012
"... necessarily reflect the views of the John Templeton ..."
Computing maximal cliques in link streams
"... Abstract A link stream is a collection of triplets (t, u, v) indicating that an interaction occurred between u and v at time t. We generalize the classical notion of cliques in graphs to such link streams: for a given ∆, a ∆clique is a set of nodes and a time interval such that all pairs of nodes ..."
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of nodes in this set interact at least once during each subinterval of duration ∆. We propose an algorithm to enumerate all maximal (in terms of nodes or time interval) cliques of a link stream, and illustrate its practical relevance on a realworld contact trace.
Approximating maximal cliques in adhoc networks
 in Proc. of PIMRC’04
, 2004
"... Abstract The capacity of an adhoc network is severely affected by interference between links, and several efforts to model this effect make use of ‘clique ’ structures in the adhoc graphs. We propose a fully distributed heuristic algorithm to approximate cliques in such networks. We further propo ..."
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Cited by 17 (1 self)
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propose methods to shrink the generated set of cliques to a set of maximal cliques. Simulation results verify the efficacy of the heuristic algorithms and also analyze their computation time.
Maximal Cliques in Unit Disk Graphs: Polynomial Approximation
 IN PROCEEDINGS INOC 2005
, 2005
"... We consider the problem of generating all maximal cliques in an unit disk graph. General algorithms to find all maximal cliques are exponential, so we rely on a polynomial approximation. Our algorithm makes use of certain key geographic structures of these graphs. For each edge, we limit the set of ..."
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Cited by 5 (2 self)
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We consider the problem of generating all maximal cliques in an unit disk graph. General algorithms to find all maximal cliques are exponential, so we rely on a polynomial approximation. Our algorithm makes use of certain key geographic structures of these graphs. For each edge, we limit the set
Finding Maximal Cliques in Massive Networks by H*graph
"... Maximal clique enumeration (MCE) is a fundamental problem in graph theory and has important applications in many areas such as social network analysis and bioinformatics. The problem is extensively studied; however, the best existing algorithms require memory space linear in the size of the input gr ..."
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Cited by 26 (14 self)
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Maximal clique enumeration (MCE) is a fundamental problem in graph theory and has important applications in many areas such as social network analysis and bioinformatics. The problem is extensively studied; however, the best existing algorithms require memory space linear in the size of the input
New Algorithms for Enumerating All Maximal Cliques
, 2004
"... Abstract. In this paper, we consider the problems of generating all maximal (bipartite) cliques in a given (bipartite) graph G = (V, E) with n vertices and m edges. We propose two algorithms for enumerating all maximal cliques. One runs with O(M(n)) time delay and in O(n 2) space and the other runs ..."
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Cited by 59 (1 self)
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Abstract. In this paper, we consider the problems of generating all maximal (bipartite) cliques in a given (bipartite) graph G = (V, E) with n vertices and m edges. We propose two algorithms for enumerating all maximal cliques. One runs with O(M(n)) time delay and in O(n 2) space and the other runs
Fast algorithms for maximal clique enumeration with limited memory
 In Proceedings of the ACM SIGKDD international
, 2012
"... Maximal clique enumeration (MCE) is a longstanding problem in graph theory and has numerous important applications. Though extensively studied, most existing algorithms become impractical when the input graph is too large and is diskresident. We first propose an efficient partitionbased algorith ..."
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Cited by 8 (5 self)
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Maximal clique enumeration (MCE) is a longstanding problem in graph theory and has numerous important applications. Though extensively studied, most existing algorithms become impractical when the input graph is too large and is diskresident. We first propose an efficient partition
The Maximal Clique and Colourability of Curve Contact Graphs
"... . Contact graphs are a special kind of intersection graphs of geometrical objects in which the objects are not allowed to cross but only to touch each other. Contact graphs of simple curves, and line segments as a special case, in the plane are considered. The curve contact representations are st ..."
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Cited by 3 (3 self)
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are studied with respect to the maximal clique and the chromatic number of the represented graphs. All possible curve contact representations of cliques are described, and a linear bound on chromatic number in the maximal clique size is proved for the curve contact graphs. 1 Intersection and contact
Image segmentation by figureground composition into maximal cliques
 In International conference on computer vision
, 2011
"... We propose a midlevel statistical model for image segmentation that composes multiple figureground hypotheses (FG) obtained by applying constraints at different locations and scales, into larger interpretations (tilings) of the entire image. Inference is cast as optimization over sets of maximal c ..."
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Cited by 17 (3 self)
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We propose a midlevel statistical model for image segmentation that composes multiple figureground hypotheses (FG) obtained by applying constraints at different locations and scales, into larger interpretations (tilings) of the entire image. Inference is cast as optimization over sets of maximal
Results 11  20
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25,404