Results 11 to 20 of about 172,035 (261)
We introduce a large equivalence class of graph properties, all of which are shared by so-called random graphs. Unlike random graphs, however, it is often relatively easy to verify that a particular family of graphs possesses some property in this class.
Chung, F. R. K. +2 more
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Degree distribution in random planar graphs [PDF]
We prove that for each $k \geq 0$, the probability that a root vertex in a random planar graph has degree $k$ tends to a computable constant $d_k$, and moreover that $\sum_k d_k =1$. The proof uses the tools developed by Gimènez and Noy in their solution
Michael Drmota, Omer Gimenez, Marc Noy
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Random Graph Isomorphism [PDF]
Summary: A straightforward linear time canonical labeling algorithm is shown to apply to almost all graphs (i.e. all but \(O(2^{\binom n2})\) of the \(2^{\binom n2})\) graphs on \(n\) vertices). Hence, for almost all graphs \(X\), and graph \(Y\) can be easily tested for isomorphism to \(X\) by an extremly naive linear time algorithm.
Babai, Laszlo +2 more
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Sigma Partitioning: Complexity and Random Graphs [PDF]
A $\textit{sigma partitioning}$ of a graph $G$ is a partition of the vertices into sets $P_1, \ldots, P_k$ such that for every two adjacent vertices $u$ and $v$ there is an index $i$ such that $u$ and $v$ have different numbers of neighbors in $P_i$. The
Ali Dehghan +2 more
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We study a random even subgraph of a finite graph $G$ with a general edge-weight $p\in(0,1)$. We demonstrate how it may be obtained from a certain random-cluster measure on $G$, and we propose a sampling algorithm based on coupling from the past. A random even subgraph of a planar lattice undergoes a phase transition at the parameter-value ${1\over2 ...
Grimmett, Geoffrey, Janson, Svante
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Bipartite Random Graphs and Cuckoo Hashing [PDF]
The aim of this paper is to extend the analysis of Cuckoo Hashing of Devroye and Morin in 2003. In particular we make several asymptotic results much more precise.
Reinhard Kutzelnigg
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We introduce a pair of natural, equivalent models for random threshold graphs and use these models to deduce a variety of properties of random threshold graphs. Specifically, a random threshold graph $G$ is generated by choosing $n$ IID values $x_1,\ldots,x_n$ uniformly in $[0,1]$; distinct vertices $i,j$ of $G$ are adjacent exactly when $x_i + x_j \ge
Reilly, Elizabeth Perez +1 more
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Random Graphs' Robustness in Random Environment
We consider configuration graphs the vertex degrees of which are independent and follow the power-law distribution. Random graphs dynamics takes place in a random environment with the parameter of vertex degree distribution following uniform ...
Marina Leri, Yury Pavlov
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9 pages, report CPTH-A264 ...
Bachas, C. +2 more
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