CSC412S Spring 2002 - Lectures

Tentative Lecture Schedule

  • Jan 7 -- Uncertainty in AI (notes)
  • Jan 9 -- Directed Graphical Models, Bayes Ball Algorithm (notes)
  • Jan 11 -- Tutorial: Probability Review (notes)
  • Jan 14 -- Undirected Models (notes)
  • Jan 16 -- CPTs, Gaussian and Exponential Distributions (notes)
  • Jan 18 -- Tutorial: Multivariate Gaussian and Assignment#1 questions
  • Jan 21 -- Statistical Parameter Estimation: Basic Models, Directed Graphs, Linear Regression (notes) (extra note)
  • Jan 23 -- Classification Models (notes)
  • Jan 25 -- Tutorial: Linear Algebra, Matrix Calculus, MATLAB
  • Jan 28 -- Tree Structured Models (notes)
  • Jan 30 -- Latent Variables, Missing Data, Mixture Models/Density, Mixtures of Experts/Conditional (notes)
  • Feb 1 -- Tutorial: Assignment#2 questions
  • Feb 4 -- EM Algorithm (1) (notes)
  • Feb 6 -- Factor Analysis (notes)
  • Feb 8 -- Tutorial: Midterm Review
  • Feb 11 -- Factor Analysis and PCA (notes)
  • Feb 13 -- EM Algorithm and Midterm Review (2) (notes)
  • Feb 15 -- MIDTERM TEST
  • Feb 18/20/22 -- READING WEEK - no classes/tutorials
  • Feb 25 -- Bayesian Statistics, Plates (notes)
  • Feb 27 -- Inference: Node Elimination (notes)
  • Mar 1 -- Tutorial: Assignment#3 questions & Midterm Handback
  • Mar 4 -- Markov and Hidden Markov Models, Dynamic Programming and Shortest Paths (notes)
  • Mar 6 -- HMM Inference and Learning (notes)
  • Mar 8 -- Tutorial: A2 solutions
  • Mar 11 -- Constrained HMMs (notes)
  • Mar 13 -- Junction Trees: Cliques, Moralization, Potential Initialization (notes)
  • Mar 15 -- Tutorial: A3 returned, A4 questions
  • Mar 18 -- Junction Trees: Triangulation, Junction Tree Construction (notes)
  • Mar 20 -- Junction Trees: Hugin Algorithm (notes)
  • Mar 21 -- NO TUTORIAL (DCS visit day)
  • Mar 25 -- Junction Tree Derivation of HMM Inference (notes)
  • Mar 27 -- Features and Maximum Entropy Models (notes)
  • Mar 29 -- NO TUTORIAL (Good Friday)
  • April 1 -- Applications: Web Document Classification, Information Retrieval (notes)
  • April 3 -- Applications: Quick Medial Reference (Quaid Morris).
  • April 5 -- Tutorial: Final Review
  • April 8 -- Catch up and Review (sample questions)
  • April 10 -- Catch up and Review
  • April 12 -- FINAL TEST


[ Home | Course Information | Lecture Schedule/Notes | Textbook/Readings | Assignments/Tests | Free Marks | Computing | ]

CSC412 - Uncertainty and Learning in Artificial Intelligence || www.cs.toronto.edu/~roweis/csc412/