matrix_and_statistical_ai_reading_group
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matrix_and_statistical_ai_reading_group [2010/03/26 13:07] 128.83.144.23 |
matrix_and_statistical_ai_reading_group [2013/04/23 21:55] (current) 127.0.0.1 converted to 1.6 markup |
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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
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