Introduction, Search & Optimization (Geoff)
| Date | Topic | Reading | Homework |
|---|---|---|---|
| Tue. 9/11 | Intro, Search | Supplemental: RN Ch 1-2 | |
| Thu. 9/13 | Search cont'd, Path planning, Randomized search | RN Ch 3-4, Supplemental: Reading on Anytime Dynamic A* |
|
| Tue. 9/18 | Propositional logic, SAT | RN Ch5, Ch 7 Supplemental: The Quest for Efficient Boolean Satisfiability Solvers. Lintao Zhang, Sharad Malik |
Problem Set 1 Out |
| Tue. 9/18 | Matlab Tutorial (5:00-6:00 1507NSH) | ||
| Thu. 9/20 | SAT+CSP cont'd, First-order logic | RN Ch 8-9 | |
| Tue. 9/25 | First-order logic cont'd, Planning | RN Ch 11-12 | |
| Thu. 9/27 | Optimization: Linear programs, Integer and Mixed-integer programs, Duality | Boyd & Vandenberghe, Ch 2-4 | |
| Tue. 10/02 | Optimization, Games | Boyd & Vandenberghe,
Ch 5, Supplemental: V. Vazirani. Approximation Algorithms. Ch 12. |
|
| Thu. 10/04 | Games | RN Ch 6 | Problem Set 1 Due 10/05 (Fri) 3:00, Problem Set 2 Out |
Learning & Probabilistic Inference (Ziv)
| Date | Topic | Reading | Homework |
|---|---|---|---|
| Tue. 10/09 | Probabilistic Reasoning and Inference | RN Ch 13 | |
| Thu. 10/11 | Learning and Inference in Bayesian Networks | RN Ch 14 | |
| Tue. 10/16 | Density Estimation | RN Ch 14 | |
| Thu. 10/18 | Inference in Hidden Markov Models | RN Ch 15 (up to and including 15.3) | Problem Set 2 Due, Problem Set 3 Out |
| Tue. 10/23 | Learning Hidden Markov Models | RN Ch 15 | |
| Thu. 10/25 | Decision Trees | RN Ch 18 | |
| Tue. 10/30 | Guest Lecture: Martial Hebert, Object Recognition | ||
| Thu. 11/01 | Natural Language Processing (not in midterm) | Problem Set 3 Due, Problem Set 4 Out | |
| Mon. 11/05 | Extra (optional) session (5:00 4602WeH) |
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| Tue. 11/06 | Neural Nets | RN 20.5 | |
| Thu. 11/08 | Markov Decision Processes (MDPs), MDP Demo | RN 17.1-17.4 | Project Proposal Due |
| Mon. 11/12 | Review session 1 (7:00-9:00 4625WeH) |
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| Tue. 11/13 | Reinforcement Learning | Problem Set 4 Due | |
| Tue. 11/13 | Review session 2 (7:00-9:00 4625WeH) |
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| Thu. 11/15 | In Class Midterm | ||
Advanced AI Applications
| Date | Topic | Reading | Homework |
|---|---|---|---|
| Tue. 11/20 | Partially Observable Markov Decision Processes (POMDPs) | Supplemental:
POMDPs for Dummies, Planning and Acting in Partially Observable Stochastic Domains |
|
| Thu. 11/22 | Thanksgiving -- No Class | ||
| Tue. 11/27 | Computational Game Theory | RN Ch 17.6-17.7 Supplemental: Osborne and Rubinstein (CMU only) |
Problem Set 5 Out |
| Thu. 11/29 | Guest Lecture: Christos Faloutsos, Graph Analysis | Beyond Streams and Graphs: Dynamic Tensor Analysis, Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint |
|
| Tue. 12/04 | Computational Biology | Progress Report Due | |
| Thu. 12/06 | Computational Biology: Cell cycles | Problem Set 5 Due 12/07 (Fri) 11:59am | |
| Thu. 12/13 | Poster session for projects (5:30-8:30 NSH atrium) | Project report due | |