Relevant bibliographies by topics / Random weighted graphs

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Academic literature on the topic 'Random weighted graphs'

Author: Grafiati
Published: 14 December 2024

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Journal articles on the topic "Random weighted graphs"

1

Komjáthy, Júlia, and Bas Lodewijks. "Explosion in weighted hyperbolic random graphs and geometric inhomogeneous random graphs." Stochastic Processes and their Applications 130, no. 3 (2020): 1309–67. http://dx.doi.org/10.1016/j.spa.2019.04.014.

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2

Vengerovsky, V. "Eigenvalue Distribution of Bipartite Large Weighted Random Graphs. Resolvent Approach." Zurnal matematiceskoj fiziki, analiza, geometrii 12, no. 1 (2016): 78–93. http://dx.doi.org/10.15407/mag12.01.078.

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3

Davis, Michael, Zhanyu Ma, Weiru Liu, Paul Miller, Ruth Hunter, and Frank Kee. "Generating Realistic Labelled, Weighted Random Graphs." Algorithms 8, no. 4 (2015): 1143–74. http://dx.doi.org/10.3390/a8041143.

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4

Amini, Hamed, Moez Draief, and Marc Lelarge. "Flooding in Weighted Sparse Random Graphs." SIAM Journal on Discrete Mathematics 27, no. 1 (2013): 1–26. http://dx.doi.org/10.1137/120865021.

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5

Amini, Hamed, and Marc Lelarge. "The diameter of weighted random graphs." Annals of Applied Probability 25, no. 3 (2015): 1686–727. http://dx.doi.org/10.1214/14-aap1034.

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6

Ganesan, Ghurumuruhan. "Weighted Eulerian extensions of random graphs." Gulf Journal of Mathematics 16, no. 2 (2024): 1–11. http://dx.doi.org/10.56947/gjom.v16i2.1866.

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The Eulerian extension number of any graph H (i.e. the minimum number of edges needed to be added to make H Eulerian) is at least t(H), half the number of odd degree vertices of H. In this paper we consider weighted Eulerian extensions of a random graph G where we add edges of bounded weights and use an iterative probabilistic method to obtain sufficient conditions for the weighted Eulerian extension number of G to grow linearly with t(G). We derive our conditions in terms of the average edge probabilities and edge density and also show that bounded extensions are rare by estimating the skewness of a fixed weighted extension. Finally, we briefly describe a decomposition involving Eulerian extensions of G to convert a large dataset into small dissimilar batches.
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7

Porfiri, Maurizio, and Daniel J. Stilwell. "Consensus Seeking Over Random Weighted Directed Graphs." IEEE Transactions on Automatic Control 52, no. 9 (2007): 1767–73. http://dx.doi.org/10.1109/tac.2007.904603.

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8

Khorunzhy, O., M. Shcherbina, and V. Vengerovsky. "Eigenvalue distribution of large weighted random graphs." Journal of Mathematical Physics 45, no. 4 (2004): 1648–72. http://dx.doi.org/10.1063/1.1667610.

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9

Mountford, Thomas, and Jacques Saliba. "Flooding and diameter in general weighted random graphs." Journal of Applied Probability 57, no. 3 (2020): 956–80. http://dx.doi.org/10.1017/jpr.2020.45.

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Abstract:
AbstractIn this paper we study first passage percolation on a random graph model, the configuration model. We first introduce the notions of weighted diameter, which is the maximum of the weighted lengths of all optimal paths between any two vertices in the graph, and the flooding time, which represents the time (weighted length) needed to reach all the vertices in the graph starting from a uniformly chosen vertex. Our result consists in describing the asymptotic behavior of the diameter and the flooding time, as the number of vertices n tends to infinity, in the case where the weight distribution G has an exponential tail behavior, and proving that this category of distributions is the largest possible for which the asymptotic behavior holds.
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10

Mosbah, M., and N. Saheb. "Non-uniform random spanning trees on weighted graphs." Theoretical Computer Science 218, no. 2 (1999): 263–71. http://dx.doi.org/10.1016/s0304-3975(98)00325-9.

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