STA 4273H (Fall 2011): Statistical Machine Learning
*** TUESDAY 9am  12PM (Room UC 376) ***
Instructor: Ruslan Salakhutdinov; email rsalakhu at utstat dot toronto dot edu
Lecture Times: Tuesday 9am  12pm
Lecture Location: UC 376
First Lecture: Sep 13, 2011
Last Lecture: Dec 06, 2011
Office hours: Fridays 1112 (TENTATIVE)
Prerequisite: Knowledge of statistical inference, probability theory, and linear algebra at the advanced undergraduate level, and some basic programming skills in R or Matlab. STA414/2104 is a plus, but is not required.
Marking Scheme
3 assignments worth 60%, one project worth 40%
Books :
Christopher M. Bishop (2006)
Pattern Recognition and Machine Learning,
Springer.
Trevor Hastie, Robert Tibshirani, Jerome Friedman (2009)
The Elements of
Statistical Learning
David MacKay (2003)
Information Theory, Inference, and Learning Algorithms
Auditing
If you are not registered in the class, it is possible for you to
audit it (sit in on the lectures), but only if you get the
instructor's permission.
Course Description
This is an advanced graduate course, designed for Master's and Ph.D. level
students, and will assume a reasonable degree of mathematical maturity.
Specific topics to be covered include:
 Linear methods for
regression/classification
 Model assessment and selection
 Graphical
models, Bayesian networks, Markov random fields, conditional random
fields
 Learning and inference in graphical models
 Approximate
variational inference, meanfield inference, loopy belief propagation
 Basic
sampling algorithms, Markov chain Monte Carlo,
Gibbs sampling, and MetropolisHastings algorithm
 Mixture models and generalized mixture models
 ExpectationMaximization
(EM) algorithm and variational EM
 Unsupervised learning, probabilistic
PCA, factor analysis, independent component analysis, and nonlinear
dimensionality reduction.
We will also discuss recent advances in machine
learning including
 Deep learning
 Deep Belief Networks and
Deep Boltzmann
Machines
 Bayesian probabilistic matrix factorization and,
 Hierarchical
Bayesian models.
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STA 4273H (Fall 2011): Research Topics In Statistical Machine Learning
 http://www.utstat.toronto.edu/~rsalakhu/sta4273/
