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/
|