Remember: there is no excuse for ignorance of the assigned reading material. Visit this page frequently. Bring a friend. Start a grassroots political movement.

Date	Topic	Reading	Out	In
Jan 9	Introduction and Overview	Chapter 1	7641 Group Project
Jan 11	Supervised Learning Review: Neural Networks & Decision Trees	Chapters 3 & 4
Jan 16	Instance Based Learning	Chapter 8	Assignment 1
Jan 18	Boosting Support Vector Machines	handouts		Team Formation
Jan 23	Support Vector Machines Boosting	handouts
Jan 25	Bayesian Learning	Chapter 6		Informal Proposal
Jan 30	Bayesian Learning
Feb 1	Bayesian Learning
Feb 6	Computational Learning Theory	Chapter 7
Feb 8	Computational Learning Theory			Formal Proposal Keywords Assignment 1 (2/9)
Feb 13	Addressing Overfitting Information Theory	Chapter 5 handouts
Feb 15	Randomized Optimization	Chapter 9	Assignment 2
Feb 20	Randomized Optimization	handouts
Feb 22	Overflow			Suggestions re: Formal Proposals (2/25)
Feb 27	Midterm Exam
March 1 Drop Day is 3/2	Exam Review
March 6	Clustering	handouts
March 8	Expectation Maximization impossibility results (clustering and NFL)	Chapter 6 (again) handouts	Assignment 3	Assignment 2 (3/9)
March 13	Feature Selection	handouts
March 15	Feature Transformation
March 19 March 23	Spring Break
March 27	Markov Decision Processes
March 29	POMDPs/Reinforcement Learning	Chapter 13		Progress Report
April 3	Reinforcement Learning		Assignment 4
April 5	Reinforcement Learning			Submitted Papers (4/6), Assignment 3 (4/8)
April 10	Game Theory	handouts
April 12	Game Theory			Review of Final Papers
April 17	Game Theory
April 19	Overflow			Final Project Material (4/22)
April 24 April 27	Final Presentations			Review of Final Presentations (4/27) Assignment 4
April 30-May 4	Final Exam Tues May 1, 11:30-2:20pm