Linear Regression and Multivariate Normal (Oct 30)
speaker: F. Pitie
Topic: it is discussed how to derive the least square estimate of a linear problem and the geometrical properties of the Multivariate Normal.
Bayesian Inference part 2 (Nov 13)
speaker: A. Kokaram
Using Markov Chain Monte Carlo : The Gibbs Sampler, Direct Numerical Sampling, Scaling Issues, Deriving Condtionals, How to spot a Gaussian, Completing the square for multidimensional variates
Hidden Markov Models (Nov 24)
speaker: Dr. Naomi Harte
This talk gives an introduction to HMMs, referring to the classic Rabiner paper. It gives ideas on how to apply HMMs to practical problems.
Markov Random Fields: A Rough Guide (Dec 3)
speaker: A. Kokaram
What are MRFs? How do you write them down? How are they used for processing fields?
Page last modified on December 04, 2008
