CMSC726 Machine Learning
Fall 2010

Schedule

For up-to-date schedule -- as well as homework assignments, handouts and slides -- please visit the ELMS site at http://elms.umd.edu
In ELMS, select the "Course Sites" tab to find this class. Then, from the left-hand menu, select "Course Documents".

Date Topic Reading Notes
Introduction
Aug 31
 Introduction and Course Overview
HW0 out
Sep 2
 ML Basics
ch. 1.1, 1.3-1.4
HW0 due
Sep 7
 Math Review & MATLAB Tutorial
ch. 1.2, Appendix C
HW1 out
Sep 9
 Decision Trees
handout
Linear Models
Sep 14
 Linear Regression
ch 3
Sep 16
 Linear Classifiers
ch 4
HW1 due
Sep 21
 Linear Models Cont.
HW2 out
Sep 23
 Generative vs. Discriminative Models
handout
Nonlinear Models
Sep 28
 Neural Networks I
ch 5
Sep 30
 Neural Networks II
ch 5
HW2 due
Oct 5
 Instance-based Learning
handout
HW3 out
Oct 7
 Support Vector Machines
ch 7.1
Oct 12
 Kernel Spaces
ch 6.1
Oct 14
 Model Evaluation
HW3 due
Oct 19
 MIDTERM EXAM
Unsupervised Learning
Oct 21
 Computational Learning Theory
handout
Oct 26
 Ensemble Methods
ch 14.3, optional reading: "boosting-schapire.pdf"
HW4 out
Oct 28
 K-Means
ch 9.1
Nov 2
 Mixture of Gaussians
ch 9.2-9.3.2,9.4
Nov 4
 Expectation Maximization
ch 9.4
HW4 due
Graphical Models
Nov 9
 Graphical Models I
ch 8
HW 5 out
Nov 14
 Graphical Models II
Nov 16
 Graphical Models III
Advanced Topics
Nov 18
 Structured Prediction, with guest lecturer, Hal Daume III
Handout: "SVM Learning for Interdependent and Structured Output Spaces"
Nov 23
 Topic Models, with guest lecturer, Jordan Boyd-Graber
Nov 30
 Reinforcement Learning
HW 5 due
Dec 2
 Reinforcement Learning / Wrap-up
Dec 7
 Project Presentations
3:30 - 6:30pm, Room AVW 2460
Dec 9
 No class
Dec 18
 FINAL EXAM, 10:30am - 12:30pm, CSI 1121

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