CSC412S Spring 2003 - Lectures
Tentative Lecture Schedule
- Jan 6 -- Uncertainty in AI, Basic Learning Problems
(notes)
- Jan 8 -- Probabilistic Graphical Models, Bayes Ball Algorithm
(notes)
- Jan 10 -- Tutorial: Probability and Statistics Review
(notes)
- Jan 13 -- Undirected Graphical Models
(notes)
- Jan 15 -- CPTs, Gaussian and Exponential Distributions
(notes)
- Jan 17 -- Tutorial: Multivariate Gaussians, Matrix Algebra and
Assignment#1 questions
- Jan 20 -- Statistical Parameter Estimation:
Basic Models, Directed Graphs, Linear Regression
(notes)
- Jan 22 -- Classification Models
(notes)
- Jan 24 -- Tutorial: Linear Algebra, Matrix Calculus, MATLAB
and Assignment #2 questions
- Jan 27 -- Tree Structured Models
(notes)
- Jan 29 -- Latent Variables, Missing Data, Mixture Models/Density, Mixtures of Experts/Conditional
(notes)
- Jan 31 -- Tutorial: Multivariate Gaussians,
Assignment#2 questions
- Feb 3 -- EM Algorithm
(notes)
- Feb 5 -- Factor Analysis and PCA
(notes)
- Feb 7 -- Tutorial: Midterm Review
- Feb 10 -- Iterative Proportional Fitting
(notes)
- Feb 12 -- Midterm Review
- Feb 14 -- MIDTERM TEST
- Feb 17-21 -- READING WEEK - no classes/tutorials
- Feb 24 -- Bayesian Statistics, Plates
(notes)
- Feb 26 -- Inference: Node Elimination
(notes)
- Feb 28 -- Tutorial: Assignment#3 questions & Midterm Handback
- Mar 3 -- Belief Propagation on Trees
(notes)
- Mar 5 -- Markov and Hidden Markov Models,
Dynamic Programming and Shortest Paths
(notes)
- Mar 7 -- A3 due today in LP283
- Mar 7 -- No Tutorial this week
- Mar 10 -- HMM Inference and Learning
(notes)
- Mar 12 -- Junction Trees: Clique Trees,
Moralization, Potential Initialization
(notes)
- Mar 14 -- Tutorial: A3 returned, A4 questions
- Mar 17 -- Junction Trees: Triangulation, Junction Tree Construction
(notes)
- Mar 19 -- Junction Trees: Final Hugin/SS Algorithms
(notes)
- Mar 21 -- Tutorial
- Mar 24 -- Junction Tree Derivation of HMM Inference
(notes)
- Mar 26 -- Features and Maximum Entropy Models
(notes)
- Mar 28 -- NOTE SPECIAL CLASS TIME
Applications(1): Web Document Classification, Information Retrieval
(notes)
- Mar 31 -- Applications(2): Quick Medical Reference, Bioinformatics
(notes)
- April 2 -- CLASS MOVED TO MARCH28
- April 4 -- Tutorial: A4 returned,
example questions for final test
- April 7 -- Factor Graphs
(notes)
- April 9 -- Catch up and Review
- April 11 -- FINAL TEST
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CSC412 - Uncertainty and Learning in Artificial Intelligence || www.cs.toronto.edu/~roweis/csc412/
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