CS 7641 & 4641
Machine Learning
Schedule

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