| Lecture |
Date |
Topic |
Reading
(textbook) |
Notes |
| 1 |
Sept 15 |
Introduction (slides: 1/page 6/page) | [RN] Chapt. 1 and 2 |
|
| 2 |
Sept 17 |
Uninformed Search (slides: 1/page 6/page) | [RN] Sect. 3.1-3.5 |
A1 out |
| 3 |
Sept 22 |
Informed Search (slides: 1/page 6/page) | [RN] Sect. 4.1-4.2 (except RBFS) |
|
| 4 |
Sept 24 |
Constraint Satisfaction Problems (slides: 1/page 6/page) | [RN] Sect. 5.1-5.2 |
|
| 5 |
Sept 29 |
Local Search (slides: 1/page 6/page) | [RN] Sect. 4.3 |
|
| 6 |
Oct 1 |
Uncertainty (slides: 1/page 6/page) | [RN] Sect. 13.1-13.6 | |
| 7 |
Oct 6 |
Bayesian Networks (slides: 1/page 6/page) | [RN] Sect. 14.1-14.2 | A1 due, A2 out |
| 8 |
Oct 8 |
Bayesian Networks (slides: 1/page 6/page) | [RN] Sect. 14.4 (except clustering algorithms) | |
| 9 |
Oct 13 |
Project ideas | |
|
| 10 |
Oct 15 |
Decision Theory (slides: 1/page 6/page) | [RN] Sect. 16.1-16.3 | |
| 11 |
Oct 20 |
Decision Networks (slides: 1/page 6/page) Note: typos in the calculations of slides 26 and 28 were corrected on Oct 27. Additional correction made to slide 28 on Nov 13. |
[RN] Sect. 16.5-16.6 | Project proposals due |
| 12 |
Oct 22 |
Probabilistic reasoning over time (slides: 1/page 6/page) | [RN] Chapt. 15 (p. 537-542,549,559) | |
| 13 |
Oct 27 |
Markov Decision Processes (slides: 1/page 6/page) | [RN] Sect. 17.1, 17.2 (up to p. 620), 17.4, 17.5 | A2 due, A3 out |
| 14 |
Oct 29 |
Decision tree learning (slides: 1/page 6/page) | [RN] Sect. 18.1-18.3 | |
| 15 |
Nov 3 |
Statistical Learning (slides: 1/page 6/page) | [RN] Sect. 20.1-20.2 (up to p. 718) | |
| 16 |
Nov 5 |
No
lecture (midterm in class) |
Midterm |
|
| 17 |
Nov 10 |
Statistical Learning (slides: 1/page 6/page) | [RN] Sect. 20.3 (up to p. 731) | |
| 18 |
Nov 12 |
Markov Networks (slides: 1/page 6/page) | Michael Jordan, Graphical Models, Statistical Science (Special Issue on Bayesian Statistics), 19, 140-155, 2004. | |
| 19 |
Nov 17 |
Condirional random fields (slides: 1/page 6/page) | Hanna M. Wallach, Conditional Random Fields: An Introduction, Technical Report MS-CIS-04-21, Department of Information Science, University of Pensylvania, 2004. | A3 due, A4 out |
| 20 |
Nov 19 |
First order logic (slides: 1/page 6/page) | [RN] Sect 7.1-7.6 [RN] Chapt. 8 and 9 |
|
| 21 |
Nov 24 |
Markov Logic Network (slides: 1/page 6/page) | Matt Richardson and Pedro
Domingos (2006), Markov
Logic Networks, Machine Learning, 62, 107-136. |
|
| 22 |
Nov 26 |
Alchemy package & Applications (slides: 1/page 6/page) | Marc Summer and Pedro Domingos (2007), The Alchemy Tutorial, Department of Computer Science and Engineering, University of Washington. | |
| 23 |
Dec 1 |
Learning and Inference with Markov Logic Network (slides: 1/page 6/page) | ||
| 24 |
Dec 3 |
Course summary (slides: 1/page 6/page) | A4 due |