Remember: there is no excuse for ignorance of the assigned reading material. Visit this page frequently. Bring a friend. Start an alternative hip-hop / bluegrass group.

Date	Topic	Reading	Out	In
Jan 6	Introduction and Overview	Chapter 1	7641 Group Project
Jan 8	Supervised Learning Review: Neural Networks & Decision Trees	Chapters 3 & 4
Jan 13	Instance Based Learning	Chapter 8	Assignment 1
Jan 15	Boosting Support Vector Machines	handouts		Team Formation (1/16)
Jan 20	Support Vector Machines Boosting	handouts
Jan 22	Bayesian Learning	Chapter 6
Jan 27	Bayesian Learning			Informal Proposal (1/25)
Jan 29	Bayesian Learning
Feb 3	Computational Learning Theory	Chapter 7
Feb 5	Computational Learning Theory			Formal Proposal (2/8) Keywords (2/8) Assignment 1 (2/8)
Feb 10	Addressing Overfitting Information Theory	Chapter 5 handouts
Feb 12	Randomized Optimization	Chapter 9	Assignment 2
Feb 17	Randomized Optimization	handouts
Feb 19	Overflow
Feb 24	Midterm Exam
Feb 26 Drop Day is 2/27	Exam Review			Suggestions re: Formal Proposals (2/27)
March 3	Clustering	handouts
March 5	Expectation Maximization impossibility results (clustering and NFL)	Chapter 6 (again) handouts	Assignment 3	Assignment 2 (3/8)
March 10	Feature Selection	handouts
March 12	Feature Transformation
March 17 March 19	Spring Break
March 24	Markov Decision Processes			Progress Report
March 26	POMDPs		Assignment 4
March 31	Reinforcement Learning	Chapter 13		Assignment 3 (4/3)
April 2	Reinforcement Learning	handouts		Submitted Papers (4/5)
April 7	Reinforcement Learning
April 9	Game Theory			Review of Final Papers (4/12)
April 14	Game Theory
April 16	Game Theory			Final Project Material (4/19)
April 21 April 23	Final Presentations			Review of Final Presentations (4/24) Assignment 4
April 27-May 1	Final Exam