"In statistics and machine learning, "model selection" is the problem of picking among different mathematical models which all purport to describe the same data set. This notebook will not (for now) give advice on it; as usual, it's more of a place to organize my thoughts and references…"

"Yet, the co-training algorithm in this paper also makes the same assumptions (as it too has underlying naive Bayes clas- sifiers), but does not suffer from the violations. Thus we hypothesize that the co-training algorithm succeeds in part because it is more robust to the assumptions made by its underlying classifiers. This can be understood by looking at the differences in how EM and co-training use the underly- ing assumptions."

"We are pleased to announce the publication of the third edition of our text, Introduction to Computer Simulation Methods by Harvey Gould, Jan Tobochnik, and Wolfgang Christian, Addison-Wesley (2006). The text introduces Java programming by example in the context of learning physics. It contains many novel applications, is accessible to a wide range of readers, develops good programming habits, and encourages student experimentation. Our goal is to teach students enough tools so that they can use computer simulations as a method of discovery in physics."

"WOB combines a database of bifurcation problems with a tutorial on nonlinear phenomena.

WOB is designed to be part of a virtual university. The approach is example-oriented and experimental. The emphasis is on examples that are application-oriented."