Welcome to the IDIAP Statistical Machine Learning Lectures

prepared by Samy Bengio

Lectures currently available:

Overview of the lectures	ps.gz	pdf
Introduction to Machine Learning	ps.gz	pdf
Statistical Machine Learning Theory	ps.gz	pdf
Classical Models	ps.gz	pdf
Artificial Neural Networks and Gradient Descent	ps.gz	pdf
Gaussian Mixture Models and Expectation-Maximization	ps.gz	pdf
Hidden Markov Models	ps.gz	pdf
Support Vector Machines	ps.gz	pdf
Ensembles Models	ps.gz	pdf
Feature Selection	ps.gz	pdf
Parameter Sharing	ps.gz	pdf

General references on each topic ps.gz pdf

Practical Informations:

How to download Torch3 from the CVS archive
Lectures:
- 21 Oct 2002, 14:00: Introduction + theoretical curves of Theoretical Section
- 31 Oct 2002, 14:00: Second part of Theoretical Section
- 7 Nov 2002, 15:00: Classical Methods
- 14 Nov 2002, 14:00: First part of Artificial Neural Networks
- 21 Nov 2002, 14:00: Second part of Artificial Neural Networks
- 28 Nov 2002, 14:00: Last part of Artificial Neural Networks
- 9 Jan 2003, 14:00: Gaussian Mixture Models
- 16 Jan 2003, 15:00: First part of Hidden Markov Models
- 23 Jan 2003, 15:00: Second part of Hidden Markov Models
- 30 Jan 2003, 15:00: Support Vector Machines
- 6 Feb 2003, 15:00: Ensemble Models
- 20 Feb 2003, 15:00: Parameter Sharing
Exercises:
- A first exercise was given:
  - copy the first lecture directory and put it in your Torch3 directory
  - go inside it and make svm
  - examine and try the script file script_svm
  - you should obtain curves similar to theoretical curves
  - try to obtain similar curves with your own dataset

__________________________________________

This website is maintained by Samy Bengio.