matrix_and_statistical_ai_reading_group
Location: ACES 3.116 Time: Wednesdays, 10-11, every other week.
Mailing list: matrix-sai at utlists.utexas
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
| Date | 24th Feb 2010. 11th Mar 2010 |
| Presenter | Pradeep Ravikumar |
Reading Material
I. Preconditioner approximations for probabilistic graphical models
| Date | 10th Feb 2010. |
| Presenter | vishvAs vAsuki |
Reading Material
1. Paper. P. Ravikumar and J. Lafferty. In Advances in Neural Information Processing Systems (NIPS) 18, pages 1113-1120, 2006.
Papers proposed
matrix_and_statistical_ai_reading_group.txt · Last modified: 2013/04/23 21:55 by 127.0.0.1
