Title: Statistical Learning II: Representation, Generalization, and
Examples.

                 Ben Recht
   Center for the Mathematics of Information
       California Institute of Technology

Abstract:  Picking up where we left off last week, I will finish describing
the fundamentals of Statistical Learning, including the discussions of
tractable function representations and generalization bounds, and present
many examples to flesh out the concepts we have been discussing.  These
examples will include several simple classification and regression tasks
that illustrate how each of the components in the learning algorithm
directly affects the learned functions.