Fall 2008

                        CS 383C / CAM 383C / Math 383E
                         "Numerical Linear Algebra"
                               MWF 9-10am
                                ENS 126

                            Prof. Inderjit Dhillon


        Matrix Computations arise in a varied number of applications, such as,
        quantum chemistry computations, statistics, economics, data mining,
        etc. This first year graduate course focuses on some of the
        fundamental computations that occur in these applications.
        The standard problems whose numerical solutions we will study
        are (i) systems of linear equations, (ii) least squares problems,
        (iii) eigenvalue problems as well as SVD computations. We will also
        learn basic principles applicable to a variety of numerical
        problems and apply them to the standard problems. These principles
        include (i) matrix factorizations, (ii) perturbation theory and
        condition numbers, (iii) effects of roundoff error on algorithms
        and (iv) analysis of the speed of algorithms.

        Pre-requisites for this course are a good knowledge of undergraduate
        linear algebra, and some mathematical sophistication (students should
        have some experience in writing mathematical proofs).

        For detailed course information see:
           http://www.cs.utexas.edu/users/inderjit/courses/cs383c