CSSS 2008 Beijing-Readings-Week-Two: Difference between revisions
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===Aaron Clauset: Power laws, Networks and Inference === | |||
The following references cover background material for the lectures. The first and second are the most relevant, with the third and fourth being additional background material on Markov chain Monte Carlo algorithms. | |||
* [[Media:CSN_07_PowerlawDistributionsInEmpiricalData_arxiv.pdf|"Power-law distributions in empirical data." Clauset, Shalizi and Newman. arXiv:0706.1062 (2007).]] | |||
* [[Media:CMN_08_Hierarchy_Preprint.pdf|"Hierarchical structure and the prediction of missing links in networks." Clauset, Moore and Newman. <i>Nature</i> <b>453</b>, 98-101 (2008).]] | |||
* [http://www-personal.umich.edu/~mejn/nbook/ <i>Monte Carlo Methods in Statistical Physics.</i> Newman and Barkema. Oxford University Press (1999).] | |||
* [http://citeseer.ist.psu.edu/andrieu03introduction.html "An Introduction to MCMC for Machine Learning." Andrieu, de Freitas, Doucet and Jordan. <i>Machine Learning</i> <b>50</b>, 5-43 (2003).] | |||
Revision as of 14:39, 27 May 2008
CSSS 2008 Beijing
|
Aaron Clauset: Power laws, Networks and Inference
The following references cover background material for the lectures. The first and second are the most relevant, with the third and fourth being additional background material on Markov chain Monte Carlo algorithms.
- "Power-law distributions in empirical data." Clauset, Shalizi and Newman. arXiv:0706.1062 (2007).
- "Hierarchical structure and the prediction of missing links in networks." Clauset, Moore and Newman. Nature 453, 98-101 (2008).
- Monte Carlo Methods in Statistical Physics. Newman and Barkema. Oxford University Press (1999).
- "An Introduction to MCMC for Machine Learning." Andrieu, de Freitas, Doucet and Jordan. Machine Learning 50, 5-43 (2003).