The following is a preliminary schedule of the lectures and presentations for CS 4033/4973/5033 Machine Learning for Fall 2006. This schedule will be updated throughout the semester as we delve deeper into special topics and/or add additional topics of interest. All readings are from Machine Learning by Tom Mitchell unless otherwise noted. The project deadlines are in red and will not change, even if other parts of the schedule change. Major new topics are noted in blue.
| Date | Topic | Assigned Reading | Assigned | Due |
| Aug 22 (Week 1) | What is Machine Learning and why should I care? | Chapter 1 (Mitchell) | ||
| Aug 24 | Function approximation | Project , HW 0 | ||
| Aug 29 (Week 2) | Reinforcement Learning, Exploration | Chapter 1 (Sutton & Barto) Optional: Chapter 13 (Mitchell) |
HW 0 | |
| Aug 31 | Exploration, The RL problem | Chapter 2 (Sutton & Barto). Skipped the starred sections. | HW 1 | Written project proposals |
| Sep 5 (Week 3) | Oral Project proposals |
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Oral project proposals | |
| Sep 7 | The RL problem | Chapter 3 (including starred section) (Sutton & Barto) | ||
| Sep 12 (Week 4) | The RL problem | HW 1 | ||
| Sep 14 | Oral reports, Dynamic Programming | Chapter 4 (Sutton & Barto) |
HW 2 | Status report 1 |
| Sep 19 (Week 5) | Temporal Difference learning | Chapter 6 (Sutton & Barto). Skip the starred sections. | ||
| Sep 21 | Advanced RL topics | |||
| Sep 26 (Week 6) | Oral reports, Neural networks | Chapter 4 (Mitchell) | HW 3 | Status report 2 |
| Sep 28 | Neural networks: backprop | HW 2 | ||
| Oct 3 (Week 7) | Neural networks | |||
| Oct 5 | Oral reports, Advanced topics in NN | Status report 3, HW 3 | ||
| Oct 10 (Week 8) | Neural net design, Overfitting |
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HW 4 | |
| Oct 12 | Evolutionary Computation: guest lecture by Dr Hougen | Chapter 9 (Mitchell) | ||
| Oct 17 (Week 9) | Oral reports, Overfitting |
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Status report 4 | |
| Oct 19 | Evolutionary computation |
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HW 4 | |
| Oct 24 (Week 10) | Learning under uncertainity | Chapter 6 (Mitchell) | HW 5 | |
| Oct 26 | Oral reports, Bayesian learning | Optional: Chapter 14 (AIMA) | Status report 5 | |
| Oct 31 (Week 11) | Bayes Nets : what they are |
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| Nov 2 | Bayes nets : how to use them | HW 5 | ||
| Nov 7 (Week 12) | Oral reports, K-means clustering (hard EM) | Status report 6 | ||
| Nov 9 | Clustering, EM for mixture models |
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| Nov 14 (Week 13) | EM for Bayes Net structure learning | HW 6 | ||
| Nov 16 | Advanced Bayesian topics | |||
| Nov 21 (Week 14) | Advanced topics by request | Preliminary writeup | ||
| Nov 23 | Thanksgiving vacation (enjoy your turkey!) |
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| Nov 28 (Week 15) | Advanced topics by request | Peer reviews | ||
| Nov 30 | Advanced topics by request | HW 6 | ||
| Dec 5 (Week 16) | Project presentations |
Final writeup (accepted to 5pm, Dec 8) | ||
| Dec 7 | Project presentations |
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| Dec 15 (Final exam period 1:30-3:30) | Project presentations |
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