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On graphs with linear Ramsey numbers
 J. GRAPH THEORY
, 2000
"... For a fixed graph H, the Ramsey number r (H) is defined to be the least integer N such that in any 2coloring of the edges of the complete graph KN, some monochromatic copy of H is always formed. Let H(n,) denote the class of graphs H having n vertices and maximum degree at most. It was shown by Chv ..."
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Cited by 34 (2 self)
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For a fixed graph H, the Ramsey number r (H) is defined to be the least integer N such that in any 2coloring of the edges of the complete graph KN, some monochromatic copy of H is always formed. Let H(n,) denote the class of graphs H having n vertices and maximum degree at most. It was shown
ON BIPARTITE GRAPHS WITH LINEAR RAMSEY NUMBERS
 COMBINATORICA 21 (2) (2001) 199–209
, 2001
"... We provide an elementary proof of the fact that the ramsey number of every bipartite graph H withmaximum degree at most ∆ is less than 8(8∆) ∆ V(H). This improves an old upper bound on the ramsey number of the ncube due to Beck, and brings us closer toward the bound conjectured by Burr and Erdős ..."
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Cited by 22 (3 self)
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We provide an elementary proof of the fact that the ramsey number of every bipartite graph H withmaximum degree at most ∆ is less than 8(8∆) ∆ V(H). This improves an old upper bound on the ramsey number of the ncube due to Beck, and brings us closer toward the bound conjectured by Burr
Subdivided graphs have linear Ramsey numbers
 J. Graph Theory
, 1994
"... It is shown that the Ramsey number of any graph with n vertices in which no two vertices of degree at least 3 are adjacent is at most 12n. In particular, the above estimate holds for the Ramsey number of any nvertex subdivision of an arbitrary graph, provided each edge of the original graph is subd ..."
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Cited by 14 (0 self)
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It is shown that the Ramsey number of any graph with n vertices in which no two vertices of degree at least 3 are adjacent is at most 12n. In particular, the above estimate holds for the Ramsey number of any nvertex subdivision of an arbitrary graph, provided each edge of the original graph
Depth first search and linear graph algorithms
 SIAM JOURNAL ON COMPUTING
, 1972
"... The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
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Cited by 1384 (19 self)
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of an undirect graph are presented. The space and time requirements of both algorithms are bounded by k 1V + k2E d k for some constants kl, k2, and k a, where Vis the number of vertices and E is the number of edges of the graph being examined.
Books in graphs
, 2008
"... A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α) ..."
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Cited by 2380 (22 self)
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A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α
Efficient GraphBased Image Segmentation
"... This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graphbased representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show that althou ..."
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Cited by 931 (1 self)
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runs in time nearly linear in the number of graph edges and is also fast in practice. An important characteristic of the method is its ability to preserve detail in lowvariability image regions while ignoring detail in highvariability regions.
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
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Cited by 801 (1 self)
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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices
High dimensional graphs and variable selection with the Lasso
 ANNALS OF STATISTICS
, 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
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Cited by 751 (23 self)
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is a computationally attractive alternative to standard covariance selection for sparse highdimensional graphs. Neighborhood selection estimates the conditional independence restrictions separately for each node in the graph and is hence equivalent to variable selection for Gaussian linear models. We
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1787 (72 self)
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A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple
A Framework for Dynamic Graph Drawing
 CONGRESSUS NUMERANTIUM
, 1992
"... Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized as follows ..."
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Cited by 627 (44 self)
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Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized
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