Sigmedia Tutorials for Postgrads

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 1 (Nov 06)

speaker: A. Kokaram

PDF Estimation and Clustering (Nov 10)

speaker: D. Corrigan

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.

An Introduction to Numerical Optimization (Dec 1)

speaker: F. Boland

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