Generating random regular graphs - C - 1984N. C. Wormald, Generating random regular graphs, Journal of Algo- rithms, 5 (1984), 247-280.Generating random regular graphs - Wormald - 1984 () Citation Context ...wn by proving that the two graph models G(N, p0) and G(N, p0; n, p1...
The R-MAT generator (Chakrabarti et al. 2004) is another popular model for generating random graphs with community structure. It is based on recursively subdividing the adjacency matrix into four equally sized partitions and distributing the edges within the partitions according to partition-specific p...
(2006) Generating simple random graphs with prescribed degree distribution. Submitted for publication.T. Britton, M. Deijfen, and A. Martin-Loeff. Generating simple random graphs with pre- scribed degree distribution. J. Stat. Phys., 124(6):1377-1397, 2006....
We show that the transition graphs of the TPSA-CA can be used to realize pseudo-random regular graphs with good expansion properties. The elegance of the scheme lies in the fact that the storage required to capture the graph is O ( log N ), where N is the total number of vertices in...
Some theorems about the convergence of graph measures are given, with applications to the calculation of the expected eigenvalue distribution of a large finite random regular or bipartite semiregular graph, and the calculation of spectral measures of several examples....
Bojchevski, Aleksandar, and Stephan Günnemann. "Deep gaussian embedding of attributed graphs: Unsupervised inductive learning via ranking." ICLR 2018.ContactPlease contact zuegnerd@in.tum.de in case you have any questions.About Implementation of the paper "NetGAN: Generating Graphs via Random ...
Once we have done everything we can to reduce noise in our measurements, and to amplify the effect we are trying to measure, the third way to increase power is to increase the sample size. The intuition behind this method is simple: With more and more measurements, random noises will tend...
The classification performance on CICIoT2023 dataset was improved by random oversampling the minority classes and undersampling the majority classes. However, the classifier with highest performance scores on the large dataset improves only in precision but not the recall. The other balancing techniques...
These indicators are susceptible to change over time as attackers use botnets, random domain names or dynamically change hash values with relative ease. On the other hand, actions of the attacker typically follow a particular sequence, which can be reused with little modification. Attributes related...
and keep only 2D information (e.g., x, y points). Further, building boundary generation component232may be configured to find concave hull points using alpha shape, fit boundary points into segmented lines using a RANdom SAmple Consensus (RANSAC) algorithm, and to merge, regularize, and ...