ISTA 410/510: Bayesian Modeling and Inference (Spring, 2012)
Lectures
Course home page
Draft slides for upcomming lectures
PDF's for upcomming lectures for those that want it. The further in the future
these go, the more likely it is that I will tweak the presentation by the time
the lecture is given. Also, there will also be bugs, errors, etc, which will get
patched in the archival versions if they are spotted in class or shortly
thereafter.
Part 01
Part 02
Part 03
Part 04
Part 05
Part 06
Supplemental Material
Introduction and Preparation
Kholar/Friedman first chapter
Kholar/Friedman second chapter
Chapter one of
Pattern Recognition and Machine Learning by Chris Bishop.
Chapter two of
Pattern Recognition and Machine Learning by Chris Bishop.
Graphical models
Chapter eight of
Pattern Recognition and Machine Learning by Chris Bishop.
EM
Chapter nine of
Pattern Recognition and Machine Learning by Chris Bishop.
Borman EM tutorial (fairly gentile coverage of EM from a formal perspective). Bishop does a similar thing using KL divergence.
HMM
Lawrence R. Rabiner,
"A Tutorial on Hidden Markov Models and Selected Applications in Speech
Recognition," Proceedings of the IEEE, 77 (2), p. 257-286, February 1989.
Chapter thirteen of
Pattern Recognition and Machine Learning by Chris Bishop.
MCMC
Andrieu, de Freitas, Doucet, and Jordan,
An Intrdoction to MCMC for Machine Learning,
2001.
Neal,
Probablistic Inference Using Markov Chain Monte Carlo Methods,
1993.
Archival Versions of Lecture Slides (with corrections)
Lecture 1 (PDF, 4 to a page)
Lecture 2 (PDF, 4 to a page)
Lecture 3 (PDF, 4 to a page)
Lecture 4 (PDF, 4 to a page)
Lecture 5 (PDF, 4 to a page)
Lecture 6 (PDF, 4 to a page)
Lecture 7 (PDF, 4 to a page)
Lecture 8 (PDF, 4 to a page)
Lecture 9 (PDF, 4 to a page)
Lecture 10 (PDF, 4 to a page)
Lecture 11 (PDF, 4 to a page)
Lecture 12 (PDF, 4 to a page)
Lecture 13 (PDF, 4 to a page)
Lecture 14 (PDF, 4 to a page)
Lecture 15 (PDF, 4 to a page)
Lecture 16 (PDF, 4 to a page)
Lecture 17 (PDF, 4 to a page)
Lecture 18 (PDF, 4 to a page)
Lecture 19 (PDF, 4 to a page)
Lecture 20 (PDF, 4 to a page)
Lecture 21 (PDF, 4 to a page)
Lecture 22 (PDF, 4 to a page)
Lecture 23 (PDF, 4 to a page)
Lecture 24 (PDF, 4 to a page)
Lecture 25 (PDF, 4 to a page)
Lecture 26 (PDF, 4 to a page)
Lecture 27 (PDF, 4 to a page)
Lecture 28 (PDF, 4 to a page)
Lecture 29 (PDF, 4 to a page)
Lecture 30 (PDF, 4 to a page)