CSC412S Spring 2006 - Lectures

Tentative Lecture Schedule

  • Jan 9 -- Uncertainty in AI, Basic Learning Problems (notes [ps.gz] [pdf])
  • Jan 11 -- Probabilistic Graphical Models, Bayes Ball Algorithm (notes [ps.gz] [pdf])
  • Jan 13 -- Tutorial: Probability and Statistics Review (notes [ps.gz] [pdf])
  • Jan 16 -- Undirected Graphical Models (notes [ps.gz] [pdf])
  • Jan 18 -- CPTs, Gaussian and Exponential Distributions (notes [ps.gz] [pdf])
  • Jan 20 -- Tutorial: Assignment#1 questions
  • Jan 23 -- Statistical Parameter Estimation: Basic Models, Directed Graphs, Linear Regression (notes [ps.gz] [pdf])
  • Jan 25 -- Classification Models (notes [ps.gz] [pdf])
  • Jan 27 -- NO TUTORIAL
  • Jan 30 -- Classification Models (again) (notes [ps.gz] [pdf])
  • Feb1 -- Tree Structured Models (notes [ps.gz] [pdf])
  • Feb 3 -- Tutorial: Assignment#2 questions
  • Feb 6 -- Latent Variables, Missing Data, Mixture Models/Density, Mixtures of Experts/Conditional (notes [ps.gz] [pdf])
  • Feb 8 -- EM Algorithm (notes [ps.gz] [pdf])
  • Feb 10 -- Tutorial: Midterm Review
    Example questions for the midterm are available in [ps] or [pdf].
  • Feb 13 -- Factor Analysis and PCA (notes [ps.gz] [pdf])
  • Feb 15 -- MIDTERM TEST 2pm sharp - 3pm
  • Feb 17 -- (lecture during tutorial time) Iterative Proportional Fitting (notes [ps.gz] [pdf])
  • Feb 20-24 -- READING WEEK - no classes/tutorials
  • Feb 27 -- Bayesian Statistics, Plates (notes [ps.gz] [pdf])
  • Mar 1 -- Inference: Node Elimination (notes [ps.gz] [pdf])
  • Mar 3 -- No Tutorial this week
  • Mar 6 -- Belief Propagation on Trees (notes [ps.gz] [pdf])
  • Mar 8 -- Markov and Hidden Markov Models, Dynamic Programming and Shortest Paths (notes [ps.gz] [pdf])
  • Mar 10 -- Tutorial: Assignment#3 questions
  • Mar 13 -- HMM Inference and Learning (notes [ps.gz] [pdf])
  • Mar 15 -- A3 due today in class
  • Mar 15 -- Inference in Profile HMMs (notes [ps.gz] [pdf])
  • Mar 17 -- No Tutorial
  • Mar 17 -- A4 posted
  • Mar 20 -- Junction Trees: Clique Trees, Moralization, Potential Initialization (notes [ps.gz] [pdf])
  • Mar 22 -- Junction Trees: Triangulation, Junction Tree Construction (notes [ps.gz] [pdf])
  • Mar 24 -- Tutorial: A4 questions
  • Mar 27 -- Junction Trees: Final Hugin/SS Algorithms (notes [ps.gz] [pdf])
  • Mar 29 -- Junction Tree Derivation of HMM Inference (notes [ps.gz] [pdf])
  • Mar 29 -- Factor Graphs (notes [ps.gz] [pdf])
  • Mar 31 -- No tutorial today.
  • Mar 31 -- A4 due today by 2pm in Pratt 283.
  • April 3 -- Features and Maximum Entropy Models (notes [ps.gz] [pdf])
  • April 5 -- Iterative Scaling (notes [ps.gz] [pdf])
  • April 7 -- Tutorial: final test questions/review
  • April 10 -- Brief Applications: Quick Medical Reference, Bioinformatics Web Document Classification, Information Retrieval (notes coming soon)
  • April 12 -- FINAL TEST


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CSC412 - Probabilistic Learning and Reasoning || www.cs.toronto.edu/~roweis/csc412/