|
Lecture Notes |
|
Syllabus and instructional objectives are also available for download. Make sure that you check the last updated notice at the bottom, since you will be responsible from the latest version at all times.
Date Topic Pre-class Lecture 0 / Math Fundamentals (Also see announcements page) September 1, 3* Introduction / Bayes Theory September 8, 10 Bayes Decision Theory September 15, 17 Density Estimation September 22, 24 PCA/FLD / Sept/Oct 29, 1 Linear Classifiers October 6, 8 Multilayer Perceptrons - EXAM I October 13, 15 RBF networks / Exam review October 20, 22 Support Vector Machines (SVM) October 27, 29 SVMs (cont.)/ Structural R.M. November 3, 5 Ensemble Learning Part I / Part II Bias-variance analysis / Diversity November 10, 12 Learn++ :Incremental / NS Learning November 17, 19 Decision Trees / CART, ID3, C4.5 November 24 EXAM II (see announcements) December 1, 3 Unsupervised Learning / Clustering December 8,10 Mixture Models / EM Alg. / RVM
December 15,17 Project Presentations
Bold: Midterm week
|
|
ECE 555 Main | Lectures | Announcements | LABS | FAQ | Related Sites |















|
Introduction to & Advanced Topics in Pattern Recognition ECE 455 /555 |