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 10	Introduction and Overview	Chapter 1	7641 Group Project
Jan 12	Supervised Learning Review: Neural Networks & Decision Trees	Chapters 3 & 4
Jan 17	Instance Based Learning	Chapter 8	Assignment 1
Jan 19	Boosting Support Vector Machines	handouts		Team Formation
Jan 24	Support Vector Machines Boosting	handouts
Jan 26	Bayesian Learning	Chapter 6		Informal Proposal
Jan 31	Bayesian Learning
Feb 2	Bayesian Learning
Feb 7	Computational Learning Theory	Chapter 7
Feb 9	Computational Learning Theory			Formal Proposal Keywords Assignment 1 (2/10)
Feb 14	Addressing Overfitting Information Theory	Chapter 5 handouts
Feb 16	Randomized Optimization	Chapter 9	Assignment 2
Feb 21	Randomized Optimization	handouts
Feb 23	Overflow			Suggestions re: Formal Proposals (2/26)
Feb 28	Midterm Exam
March 2 Drop Day is 3/3	Exam Review
March 7	Clustering	handouts
March 9	Clustering Expectation Maximization	Chapter 6 (again) handouts	Assignment 3	Assignment 2 (3/10)
March 14	Feature Selection	handouts
March 16	Feature Transformation
March 21 March 23	Spring Break
March 28	Markov Decision Processes
March 30	POMDPs/Reinforcement Learning	Chapter 13		Progress Report
April 4	Reinforcement Learning		Assignment 4
April 6	Reinforcement Learning			Submitted Papers (4/7), Assignment 3 (4/9)
April 11	Game Theory	handouts
April 13	Game Theory			Review of Final Papers
April 18	Game Theory
April 20	Overflow			Final Project Material (4/22)
April 25 April 27	Final Presentations			Review of Final Presentations (4/28) Assignment 4
May 1-5	Final Exam