Teaching Courses

My recipe for teaching advanced topics in Computer Vision, Pattern Recognition and Machine Learning:

I divide the literature into three methods:

1. descriptive, 2. generative, and 3. discriminative.

Each method include two aspects:

a. representation, and b. computation.

Thus things fall into a 2x3 table. I organize them in three classes below.

	descriptive	generative	discriminative
representation	Stat232A-CS266A	Stat232A-CS266A	Stat231-CS276A
computation	Stat232B-CS266B	Stat232B-CS266B	Stat231-CS276A

University of California, Los Angeles (Statistics cross-listed with Computer Science)

Stat231-CS276A	Pattern Recognition and Machine Learning
Stat232A-CS266A	Statistical Modeling and Learning in Vision and Image Science
Stat232B-CS266B	Statistical Computing and Inference in Vision and Image Science