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|Title:||Generating random graphic sequences|
|Source:||Lu, X.,Bressan, S. (2011). Generating random graphic sequences. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6587 LNCS (PART 1) : 570-579. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-20149-3_41|
|Abstract:||The graphs that arise from concrete applications seem to correspond to models with prescribed degree sequences. We present two algorithms for the uniform random generation of graphic sequences. We prove their correctness. We empirically evaluate their performance. To our knowledge these algorithms are the first non trivial algorithms proposed for this task. The algorithms that we propose are Markov chain Monte Carlo algorithms. Our contribution is the original design of the Markov chain and the empirical evaluation of mixing time. © 2011 Springer-Verlag.|
|Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Appears in Collections:||Staff Publications|
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