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/