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/