- Administrivia .
- Mitchell, Machine Learning, Chapter 1 draft: Introduction
- Mitchell, Machine Learning, Chapter 2 draft: Concept Learning
- Kearns, Li, Pitt, Valiant: "Recent results on boolean concept learning".
- Littlestone: "Learning quickly...".
- Mitchell, Machine Learning, Chapter 3 draft: Decision Tree Learning
- Murphy, P.M. and Pazzani, M.J. (1994)
"Exploring the Decision Forest: An Empirical Investigation of Occam's
Razor in Decision Tree Induction", Journal of AI Research, Volume
1, pages 257-275.
- Rivest's lecture notes on Bayesian inference.
- Selection from Minsky and Papert, Perceptrons.
- Rumelhart, Hinton, and Williams "Learning internal representations by error propagation" Chapter 8 of Parallel Distributed Processing, Rumelhart and McClelland.
- Mitchell, et. al.,
"Experience with a Learning Personal Assistant", CACM, July, 1994.
- Lang, Waibel, and Hinton, "A time-delay neural network architecture for
isolated word recognition" Neural Networks, (3), pp. 33-43, 1990.
- Mitchell, Machine Learning, Chapter 8 draft: Genetic Algorithms
- Mitchell, Machine Learning, Chapter 6 draft: Analytical Learning
- Mitchell and Thrun,
"Explanation-Based Learning: A Comparison of Symbolic and Neural Network
Approaches", Tenth Int. Conf. on Machine Learning, June, 1993.
- Watkins and Dayan, "Q-learning".
- Rivest and Schapire, "Inference of Finite Automata using Homing
Sequences", Inf.&Comp. 103, 1993.
Lecture slides (when available):
Copies of handouts can be picked up in Jean Harpley's office: Wean Hall 5313.
- Assignment 1: Due Sept 8. Problems 1 and 2 from Chapter 2.
- Assignment 2 . Due Sept 15.
Note: in problem 1(b), you may use O( ) notation in your answer. Also,
in problem 4, the reference should be to 1(a), not 2(a).
- Assignment 3.
Decision tree learning of calendar scheduling preferences.
Due October 4. See also /afs/cs/project/theo-1/assignment/README.
Click here to see
code/results/observations that students have made available.
- Assignment 4. Due October 25. ( solutions )
Assignment 5. Face recognition. Due November 8.
What to hand in. The full materials (training images,
Backpropagation source code, etc.) are available
- Assignment 6. Reinforcement learning. ( solutions )