I'm trying to write a new computer vision textbook. I'm going to post updated versions here as I do so. The plan is to first teach probability and machine learning and then present each chapter as a different model with associated learning and inference algorithms.
Thursday, July 22, 2010
I've been sketching out the regression chapter. I'm going to cover linear regression, Bayesian linear regression (i.e. GPs), kernel methods and the relevance vector machine. I'm still hunting around for some good applications to illustrate this all with.