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CSC412S/2506S Spring 2004 - Lectures
Tentative Lecture Schedule
- Jan 5 -- Uncertainty in AI, Basic Learning Problems
(notes [ps,
pdf])
- Jan 7 -- Probabilistic Graphical Models, Bayes Ball Algorithm
(notes [ps,
pdf])
- Jan 9 -- Tutorial: Probability and Statistics Review
(notes)
- Jan 12 -- Undirected Graphical Models
(notes [ps,
pdf])
- Jan 14 -- CPTs, Gaussian and Exponential Distributions
(notes [ps,
pdf])
- Jan 16 -- Tutorial: Multivariate Gaussians, Matrix Algebra and
Assignment#1 questions
see
this note
and
this one.
- Jan 19 -- Statistical Parameter Estimation:
Basic Models, Directed Graphs, Linear Regression
(notes [ps,
pdf])
- Jan 21 -- Classification Models
(notes [ps,
pdf])
- Jan 23 -- Tutorial: Linear Algebra, Matrix Calculus, MATLAB
and Assignment #2 questions
- Jan 26 -- Tree Structured Models
(notes [ps,
pdf])
- Jan 28 -- Latent Variables, Missing Data, Mixture Models/Density, Mixtures of Experts/Conditional
(notes [ps,
pdf])
- Jan 30 -- Tutorial: Multivariate Gaussians,
Assignment#2 questions
- Feb 2/4 -- EM Algorithm
(notes [ps,
pdf])
- Feb 6 -- Tutorial: Midterm Questions/Review
- Feb 9 -- Factor Analysis and PCA
(notes [ps,
pdf])
- Feb 11 -- Iterative Proportional Fitting
(notes [ps,
pdf])
- Feb 11 -- Factor Graphs
(notes [ps,
pdf])
- Feb 13 -- MIDTERM TEST
- Feb 16-20 -- READING WEEK - no classes/tutorials
- Feb 23 -- Bayesian Statistics, Plates
(notes [ps,
pdf])
- Feb 25 -- Inference: Node Elimination
(notes [ps,
pdf])
- Feb 27 -- NO Tutorial
- Mar 1 -- Belief Propagation on Trees
(notes [ps,
pdf])
- Mar 3 -- Junction Trees: Clique Trees,
Moralization, Potential Initialization
(notes [ps,
pdf])
- Mar 5 -- Tutorial: Assignment#3 questions & Midterm Handback
- Mar 8 -- A3 due today in class
- Mar 8 -- Markov and Hidden Markov Models,
Dynamic Programming and Shortest Paths, Inference (Forward-Backward)
(notes [ps,
pdf])
- Mar 10 -- Profile HMMs, Baum Welch (EM) updates
(notes [ps,
pdf])
- Mar 12 -- NO Tutorial
- Mar 15 -- Junction Trees: Triangulation, Junction Tree Construction
(notes [ps,
pdf])
- Mar 17 -- Junction Trees: Final Hugin/SS Algorithms
(notes [ps,
pdf])
- Mar 19 -- Junction Tree Derivation of HMM Inference
(notes [ps,
pdf])
- Mar 22 -- Tutorial: A4 questions
- Mar 24 -- Features and Maximum Entropy Models
(notes [ps,
pdf])
- Mar 29 -- A4 due today in class
- Mar 29 -- Iterative Scaling
(notes [ps,
pdf])
- Mar 31 -- Applications(1): Web Document Classification,
Information Retrieval
(notes [ps,
pdf])
- April 2 -- GB304 NOTE SPECIAL CLASS TIME (TUTORIAL MOVED TO APRIL 5)
April 2 -- Applications(2): Quick Medical Reference, Bioinformatics
(notes [ps,
pdf])
- April 5 -- Tutorial: (NOTE SPECIAL TIME; CLASS MOVED TO APRIL 2)
A4 returned, example questions for final test
- April 7 -- FINAL TEST IN CLASS
- April 9 -- Good Friday, University Closed
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CSC412/2506 - Uncertainty and Learning in Artificial Intelligence || www.cs.toronto.edu/~roweis/csc412/
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