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matrix_and_statistical_ai_reading_group [2010/03/26 13:07]
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matrix_and_statistical_ai_reading_group [2013/04/23 21:55] (current)
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 === III === === III ===
-|Pradeep Ravikumar et al: High-dimensional covariance estimation by minimizing l_1-penalized log-determinant divergence http://​www.stat.berkeley.edu/​tech-reports/​767.pdf| | +|Date | 31 Mar 2010. | 
-|Matyas Sustik | | +|Paper ​| Pradeep Ravikumar et al: High-dimensional covariance estimation by minimizing l_1-penalized log-determinant divergence http://​www.stat.berkeley.edu/​tech-reports/​767.pdf| | 
-|This paper contains a good introduction to covariance matrix estimation; the "large p small n case"; the connection to logdet divergence before delving into its main results. | |+|Presenter ​| Matyas Sustik | | 
 +|Notes ​| This paper contains a good introduction to covariance matrix estimation; the "large p small n case"; the connection to logdet divergence before delving into its main results. | |
  
 === II. Intro to the use of Support graphs in finding preconditioners === === II. Intro to the use of Support graphs in finding preconditioners ===
matrix_and_statistical_ai_reading_group.1269626856.txt.gz · Last modified: 2010/03/26 13:07 by 128.83.144.23