New for: D1
into algorithms used in applied statistics and pattern recognition.
One prominent example are methods for nonlinear dimension reduction,
which are closely related to the geometric problem of reconstructing
manifolds from a finite set of samples. This talks surveys some
recent developments in both fields, with an emphasis on the problem of
modeling the <I>local</I> structure of points sets using proximity
graphs.