Computer Science 246/446

Mathematical Foundations of Artificial Intelligence

Spring 2005

Instructor: Dan Gildea
TA: Hao Zhang
Location: TTh 11:05am-12:20pm, CSB 703.

Homeworks

Text: David J. C. MacKay, Information Theory, Inference, and Learning Algorithms
Recommended: Trevor Hastie, Robert Tibshirani, Jerome Friedman, The elements of statistical learning: data mining, inference, and prediction. Dana Ballard, Natural Computation.

Syllabus

Onwe will coverwhich means that after class you will understandif before class you have read
1/13 Introduction
1/18 Probability Theory independence, bayes rule charniak
1/20 Information Theory entropy, kl-distance, coding mackay ch 2
1/25 Probabilistic Inference priors: bayesian reasoning, MAP heckerman
1/27 Probabilistic Inference priors on continuous variables mackay ch 24
2/1 Minimum Description Length decision trees mackay ch 28
2/3 Probabilistic Inference polytree mackay ch 26
2/8 Expectation Maximization latent variable clustering bilmes § 1-3
2/10 Independent Component Analysis source separation mackay ch 34
2/15 Learning Theory probably approximately correct kearns&vazirani ch 1
2/17 Learning Theory VC dimension kearns&vazirani ch 2, 3
2/22 Eigenvectors least squares, PCA bishop 310-314, appendix E
2/24 Nonlinear Dimensionality Reduction isomap, locally linear embedding roweis; tenenbaum
3/1 Optimization conjugate gradient shewchuk § 1-9
3/3 Optimization Gibbs Sampling, MCMC mackay ch 29
3/15 Review
3/17 Midterm
3/22 Midterm Solutions aspect model
3/24 MCMC, Gibbs (continued from before midterm) mackay ch 38, 39
3/29 Backpropagation the chain rule bishop 140-148
3/31 Support Vectors the wolfe dual hastie ch 12
4/5 Support Vectors the kernel trick
4/7 Hidden Markov Models forward-backward ballard ch 10; bilmes § 4
4/12 Reinforcement Learning q-learning ballard ch 11
4/14 Reinforcement Learning partial observability ballard ch 11
4/19 Games dana ballard
4/21 Games learning to co-operate hauert, zhu
4/26 Review come to class with questions!
Final Exam: Friday May 6, 8:30am, CSB 632.

Supplemental Reading

Grading


gildea @ cs rochester edu
April 25, 2005