# Difference between revisions of "Aaron Clauset"

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* [[Media:CSN_07_PowerlawDistributionsInEmpiricalData_arxiv.pdf|"Power-law distributions in empirical data." A. Clauset, C. R. Shalizi and M. E. J. Newman. arXiv:0706.1062 (2007).]] | * [[Media:CSN_07_PowerlawDistributionsInEmpiricalData_arxiv.pdf|"Power-law distributions in empirical data." A. Clauset, C. R. Shalizi and M. E. J. Newman. arXiv:0706.1062 (2007).]] | ||

− | * [http://siamdl.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=SIREAD000045000002000167000001 "The | + | * [http://siamdl.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=SIREAD000045000002000167000001 "The structure and function of complex networks." M. E. J. Newman, ''SIAM Review'' '''45''', 167-256 (2003)] |

## Revision as of 22:35, 15 July 2008

Aaron Clauset [homepage] has been a post-doctoral fellow at the Santa Fe Institute since 2006 and is an alumnus of the CSSS 2003 (Santa Fe).

### Santa Fe School

This year, Clauset will deliver a lecture on Markov chain Monte Carlo methods for simulation and inference in complex systems. To be best prepared for the lecture, you should take a look at these papers. The first is the most relevant, with the others being more background material.

- "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).

### Beijing School

Clauset will deliver three lectures; two will cover the basics of complex networks and network analysis, and one will cover the estimation and validation of power-law distributions in empirical data. To be best prepared for the lecture, you should take a look at these two papers.