Computer Science 246/446

Mathematical Foundations of Artificial Intelligence

Spring 2006

Instructor: Dan Gildea office hours 1-2pm Wed
TA: Ding Liu office hours 9:30-11am Tu/Th
Location: Tu/Th 11:05am-12:20pm, CSB 601


There is no required text, but the following are useful references in addition to the reading material assigned for each class:

Readings for each class are available in the box in the CS mailroom.


Onwe will coverwhich means that after class you will understandif before class you have read
1/19 Probability Theory independence, bayes rule wasserman ch 1, 2, 3
1/24 Information Theory entropy, kl-distance, coding mackay ch 2
1/26 Probabilistic Inference priors: bayesian reasoning, MAP heckerman
1/31 Probabilistic Inference priors on continuous variables mackay ch 24
2/2 Minimum Description Length decision trees mitchell
2/7 Probabilistic Inference polytree mackay ch 26
2/9 Expectation Maximization latent variable clustering bilmes §1-3
2/14 Independent Component Analysis source separation mackay ch 34
2/16 Learning Theory probably approximately correct kearns&vazirani ch 1
2/21 Learning Theory VC dimension kearns&vazirani ch 2, 3
2/23 Eigenvectors least squares, PCA bishop 310-314, appendix E
2/28 Nonlinear Dimensionality Reduction isomap, locally linear embedding roweis; tenenbaum
3/2 Optimization conjugate gradient bishop 274-282
3/7 Optimization Gibbs Sampling, MCMC mackay ch 29
3/9 Review
3/21 Midterm
3/23 Midterm Solutions
3/28 MCMC, Gibbs (continued from before midterm)
3/30 Perceptron, Backpropagation the chain rule mackay ch 38, 39; bishop 140-148
4/4 Support Vectors the wolfe dual burges §3-4
4/6 Support Vectors the kernel trick
4/11 Hidden Markov Models forward-backward bilmes §4
4/13 Reinforcement Learning q-learning ballard ch 11
4/18 Reinforcement Learning partial observability ballard ch 11
4/20 Games nash equilibrium morris 115-131
4/25 Games learning to co-operate
4/27 Something Fun
5/2 Review come to class with questions!
Final Exam: Friday May 12, 8:30am.


gildea @ cs rochester edu
April 11, 2006