recitation tomorrow
7 views
Skip to first unread message
percy...@gmail.com
Sep 30, 2007, 11:35:18 PM9/30/07
to CS281A: Statistical Learning Theory (Fall 2007)
At tomorrow's recitation (4:30-6 in Soda 306), I plan to cover the
following:
- Derive the posterior for the mean of a Gaussian (with a Gaussian
prior)
- Derive the posterior for the variance of a Gaussian (with an
inverse Gamma prior)
- Derive the posterior for the parameters of a multinomial (with a
Dirichlet prior)
- Maximum likelihood estimation of multinomial parameters (using
Lagrangian multipliers)
following:
- Derive the posterior for the mean of a Gaussian (with a Gaussian
prior)
- Derive the posterior for the variance of a Gaussian (with an
inverse Gamma prior)
- Derive the posterior for the parameters of a multinomial (with a
Dirichlet prior)
- Maximum likelihood estimation of multinomial parameters (using
Lagrangian multipliers)
-Percy
Reply all
Reply to author
Forward
0 new messages