CS472 - Fall 2007
Cornell University
Department of Computer Science

• Monday, 11:15am - 12:05pm in PH219
• Wednesday, 11:15am - 12:05pm in PH219
• Friday, 11:15am - 12:05pm in PH219

First Prelim Exam: Friday, September 28.
Second Prelim Exam: Monday, November 19.
Final Exam: Monday, December 10, 9:00am - 11:30am, Location OH255

[cs472-l@cs.cornell.edu] We'd like you to contact us by using this mailing list.  The list is set to mail all the TA's and Prof. Joachims -- you will get the best response time by using this facility, and all the TA's will know the question you asked and the answers you receive.
[CS472 Wiki] This is our Wiki. If you cannot view it, let us know. We may post important things here. Feel free to post important things here as well, though obviously without dishonoring Cornell's academic principles.

• Introduction of AI and background: What is AI? Related fields
• Problem solving by search: principles of search, uninformed (“blind”) search, informed (“heuristic”) search, genetic algorithms, game playing
• Learning: inductive learning, concept formation, decision tree learning, statistical approaches, neural networks
• Knowledge representation and reasoning: knowledge bases and inference; constraint satisfaction; planning; theorem-proving; Bayesian networks
• Natural language understanding: syntactic processing, ambiguity resolution, text understanding

• 08/24: R&N Chapter 1
• 08/27: R&N Chapter 2
• 08/31: R&N Chapter 3
• 09/03: R&N 4.1-4.2.
• 09/07: R&N 4.3. and p. 120.
• 09/12: R&N Chapter 5
• 09/17: R&N Chapter 6
• 09/21: R&N 17.1
• 09/24: R&N 17.2-17.3
• 09/26: R&N 21.1-21.4
• 10/03: R&N 18.1-18.2, 20.4
• 10/10: R&N 18.3
• 10/17: R&N 18.5
• 10/22: R&N 20.5 (single layer)
• 10/24: Schoelkopf & Smola 7.1-7.3, 7.5 (online)
• 10/26: R&N 20.5 (remainder)
• 10/31: R&N 20.6-20.7, Schoelkopf & Smola 7.4 (online)
• 11/02: Optimizing Search Engines Using Clickthrough Data (online)
• 11/07: R&N 7.1-7.5
• 11/09: R&N 7.6
• 11/12: R&N Chapter 8
• 11/14: R&N 9.1-9.3, 9.5
• 11/21: R&N 10.3 (up to page 334)
• 11/26: R&N 11.1-11.2
• 11/28: R&N 11.3

08/24: Introduction (PDF)
• 08/27: Agents and Problem-Solving as Search (PDF)
• 09/03: Informed Search (PDF)
• 09/07: Local Search (PDF)
• 09/12: Constraint Satisfaction (PDF)
• 09/17: Adversarial Search and Games (PDF)
• 09/21: Markov Decision Processes and Reinforcement Learning (PDF)
• 10/03: Instance Based Learning (PDF)
• 10/10: Decision Trees (PDF)
• 10/15: Overfitting and Cross-Validation (PDF)
• 10/17: Statistical Learning Theory (PDF)
• 10/22: Perceptron and Optimal Hyperplanes (PDF)
• 10/26: Neural Nets (PDF)
• 10/31: Support Vector Machines and Kernels (PDF)
• 11/02: Learning Rankings for Search Engines (PDF)
• 11/07: Knowledge-Based Systems (PDF)
• 11/12: First-Order Logic and Resolution (PDF)
• 11/21: Planning (PDF)

Homework assignments are available via CMS. Assignments are due in hardcopy. Graded homework assignments and the prelims can be picked-up in Upson 360. The opening hours are Monday-Friday, 10am-12pm and 2pm-4pm (check: are these still the current times?).

See critique guidelines and samples on the Wiki.

• 25%: 2 Prelim Exams
• 25%: Final Exam
• 45%: Homework (~6 assignments)
• 5%: Participation

All assignments are due at the beginning of class on the due date. Assignments turned in late will drop 5 points for each period of 24 hours for which the assignment is late. In addition, no assignments will be accepted after the solutions have been made available.

Roughly: A=92-100; B=82-88; C=72-78; D=62-68; F= below 60

Although you are encouraged to talk with any TA about the questions, only Tom the TA may award back points (or detract points if his eagle eyes find new things wrong) if you want a regrade.