Tentative Schedule for Machine Learning 2004

Week	Readings (in Mitchell unless otherwise stated)	Scribe
1, Jan 6/8	Ch. 1. Introduction.
2, Jan 13/15	Ch.2. Concept Learning. Ch. 3.1-3.7.1. Decision Tree Learning.
3, Jan 20/22	Ch. 3.1-3.7.1. Decision Tree Learning.	Pkerskaya, Irena Maryan Bavarian Ladan Hababodic
4, Jan 27/29	Neural Nets: Ch. 4.1-4.4.4, 4.5-4.9	Paul Rajashree Wendy Wang Ming Zhou
5, Feb 3/5	Neural Nets: Ch. 4.1-4.4.4, 4.5-4.9	Sarah Brown Angie Zhang
6, Feb 10/12	Bayesian Learning. Ch. 6.1-6.10	Kam-Sing Leung Jiang Ye Byron Gao
7, Feb 19	Finish Bayesian Learning. Learning Bayes Nets. Ch. 6.11.	Steven Bergner Chris Demwell
8, Feb 24/26	Finish Bayes Nets.	Alison Meynert Calvin Tang Alan Chou
9, March 2/4	Evaluating Statistical Hypotheses. Ch 5.	Hongyin Cui Yinan Zhang
10, March 9/11	Finish Evaluating Hypotheses. The EM algorithm. Ch. 6.12.	Chidan Cheng Yan Long
11, March 16/18	Reinforcement Learning. Ch. 13.	M. Soliman Lina Bjornheden
12, March 23/25	Finish Reinforcement Learning.	Jakob von Recklinghausen
13, 3/11,4/1	Inductive Logic Programming. Ch. 10.	Gabor
13, April 6	Finish ILP.