| Syllabus | Schedule | FAQ | Assignments | My home page |
| Section 01: | Monday 05:30 PM - 06:45 PM, Wednesday 05:30 PM - 06:45 PM | Class Number:3031/3032 |
| Healey Library Low Level H-LL-3507 | ||
| Weeks | Meetings | Topic | Readings & Handouts | Examples & Web Resources |
|---|---|---|---|---|
| 1. | Sept. 5, no class, Labor Day (Holiday) | |||
| Sept. 7 | Course Administration | |||
| 2. | Sept. 12 | Introduction to AI |
Ch 1 Slide: Introduction to AI |
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| Sept. 14 | Solving Problem by Searching |
Ch 3.1 ~ Ch 3.3 Slides: Solving Problem by Searching |
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| 3. | Sept. 19 | Uninformed Search Strategies |
Ch 3.4 ~ Ch 3.5 Slides: Uninformed Search Strategies |
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| Sept. 21 | Presentation of Homework Assignment 1 | |||
| 4. | Sept. 26 | Uninformed Search Strategies (continued) Informed Search and Exploration |
Ch 4 Slides: Informed Search and Exploration Part I |
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| Sept. 28 | Informed Search and Exploration
(continued) |
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| 5. | Oct. 3 | Informed Search and Exploration (continued) | Slides: Informed Search and Exploration Part II | |
| Oct. 5 | Informed Search and Exploration (continued) | |||
| 6. | Oct. 10, no class, Columbus Day (Holiday) | |||
| Oct. 12 | Informed Search and Exploration (continued) | Slides: Informed Search and Exploration Part III | ||
| 7. | Oct. 17 | Informed Search and Exploration (continued) | ||
| Oct. 19 | Uncertainty | Slides: Uncertainty | ||
| 8. | Oct. 24 | Programming Assignment 2 Presentation |
Ch 13 ~ Ch 14, Ch 20.2 Slides: Uncertainty |
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| Oct. 26 | Kyle McGivney and Chrisopher Griffith: Discussion of Programming Assignment 1 (writing AI algorithms in OOD)
Uncertainty |
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| 9. | Oct. 31 | Uncertainty(continued) |
Pre-Exam Review |
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| Nov. 2 | Midterm Examination |
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The Official US Time | |
| 10. | Nov. 7 |
Classification KNN |
Slides: Classification KNN | |
| Nov. 9 | Binh D. Tran: Leakage in Data Mining: Formulation, Detection, and Avoidance (KDD 2011) Uncertainty(continued) |
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| 11. | Nov. 14 | Dawei Wang:
How Good is Almost Perfect?
(AAAI 2008) Probabilistic Reasoning over Time (continued) |
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| Nov. 16 | Pothan Chand Yarra:
Optimal False-Name-Proof Voting Rules with Costly Voting (AAAI 2008) Learning Probabilistic Models |
Ch 20 | ||
| 12. | Nov. 21 | Mingbo Ma: Hilbert Space Embeddings of Hidden Markov Models (ICML 2010) Learning Probabilistic Models (continued) | ||
| Nov. 23 | Kyle McGivney: A probabilistic framework for semi-supervised clustering (KDD 2004) Learning Probabilistic Models (continued) | |||
| 13. | Nov. 28 | Classification: Basic Concepts | ||
| Nov. 30 | Classification: Nearest-Neighbor Classifiers | |||
| 14. | Dec. 5 | Classification: Decision Trees | ||
| Dec. 7 | Classification: Ensemble Methods | |||
| 15. | Dec. 12 | Final Exam | ||
| Dec. 14 | Reading day (no class) | |||
| 16. | Dec. 19 (6:30PM -9:30PM)) | Homework Presentation (Monday, 6:30-9:30 PM, Dec 19, 2011, Wheatley W01-0037) | ||
| Top |
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