Theme of LMIPO

Polynomial optimization is an important topic in mathematical programming theory and applications. It is often NP-hard. Recently, linear matrix inequality and semidefinite programming techqniues prove very efficient in finding global optimal solution for polynomial optimization problems. They bring interesting interations between mathematical areas like convex analysis, optimization theory, moment theory, and algebraic geometry. This workshop will be an introduction to the mathematical tools required to do research in this area. Little background is required; indeed the tutorials will be understandable to graduate students.

Lecturers

Pablo Parrilo (MIT)

Mihai Putinar (UCSB)

Bernd Sturmfels (UC Berkeley)

Rekha Thomas (Univ. Washington)

Topics of LMIPO

Linear Matrix Inequalities

Semidefinite Programming

Sum of Squares and Nonnegative Polynomials

Geometry of Spectrahedra

Positivstellensatz and Moment Theory

Applications

This tutorial workshop is funded by NSF Grant DMS-0844775.

Limited financial supports are available for student participants who need travel support. Interesting students needing financial supports please apply by sending email to Jiawang Nie. In the email, please indicate the applicant's name, institution and department, research area, the name and email address of the student's advisor (who we possibly will contact).

The deadline of the application is November 30, 2009.

Contact Information

  Organizer:
    Jiawang Nie (njw AT math.ucsd.edu)
  Co-Organizer:
    Bill Helton (helton AT math.ucsd.edu)

  Mailing address:
    Jiawang Nie
    UCSD  Mathematics Department
    9500 Gilman Drive
    La Jolla, CA 92093  

    Phone number: (858)534-6015