matrix_and_statistical_ai_reading_group
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| Mailing list: matrix-sai at utlists.utexas | Mailing list: matrix-sai at utlists.utexas | ||
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| + | === III === | ||
| + | |Date | 31 Mar 2010. | | ||
| + | |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| | | ||
| + | |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 === | ||
| - | | Date | 24th Feb 2010. 11th Mar 2010 | + | | Date | 24th Feb 2010. 11th Mar 2010 | |
| - | | | + | |
| |Presenter | Pradeep Ravikumar | | |Presenter | Pradeep Ravikumar | | ||
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| Reading Material | Reading Material | ||
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| ===== Papers proposed ===== | ===== Papers proposed ===== | ||
| - | |Paper | | | ||
| - | |Proposer | | | ||
| - | |Why? | | | ||
matrix_and_statistical_ai_reading_group.1267730763.txt.gz · Last modified: 2010/03/04 13:26 by 128.83.144.23
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