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/
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