|Convexity and Fixed Point Algorithms in Hilbert Space|
My aim is to present a largely self-contained account of convex
analysis and optmization in Hilbert space, and to provide a concise
exposition of the large body of related constructive fixed point
theory that has become indispensible in applications.
The central theme is the interplay among convexity,
monotonicity, and nonexpansivity. Topics covered (in varying
levels of detail) are: convex sets and cones; convex functions;
Fenchel conjugates and duality; subdifferentiability; convex
optimization; monotone operators; nonexpansive operators and
generalizations; algorithms for convex feasibility and best
|Integral geometry of convex bodies and polyhedra|
Prerequisites: undergraduate level real analysis and linear algebra
We will cover the following topics, as time permits:
|The Mathematics of Finance|
It is intended to cover the following topics :
Required textbook: Bickel, P. and Doksum, K. Mathematical Statistics: Basic Ideas and Selected Topics, Vol. I, Second Edition, Prentice Hall.
The pre-requisites for this course are a knowledge of multivariable calculus, and linear algebra.
The course will provide an introduction to the methods of mathematical statistics.
The following is an outline of topics to be covered, and associated sections from the book.