Adam Andrzej Kurpisz: Catalogue data in Spring Semester 2021 |
Name | Dr. Adam Andrzej Kurpisz |
Address | Institut für Operations Research ETH Zürich, HG G 22.1 Rämistrasse 101 8092 Zürich SWITZERLAND |
Telephone | +41 44 632 40 17 |
adam.kurpisz@ifor.math.ethz.ch | |
URL | http://n.ethz.ch/~kurpisza/ |
Department | Mathematics |
Relationship | Lecturer |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
401-3908-21L | Polynomial Optimization | 6 credits | 3G | A. A. Kurpisz | |
Abstract | Introduction to Polynomial Optimization and methods to solve its convex relaxations. | ||||
Objective | The goal of this course is to provide a treatment of non-convex Polynomial Optimization problems through the lens of various techniques to solve its convex relaxations. Part of the course will be focused on learning how to apply these techniques to practical examples in finance, robotics and control. | ||||
Content | Key topics include: - Polynomial Optimization as a non-convex optimization problem and its connection to certifying non-negativity of polynomials - Optimization-free and Linear Programming based techniques to approach Polynomial Optimization problems. - Introduction of Second-Order Cone Programming, Semidefinite Programming and Relative Entropy Programming as a tool to solve relaxations of Polynomial Optimization problems. - Applications to optimization problems in finance, robotics and control. | ||||
Lecture notes | A script will be provided. | ||||
Literature | Other helpful materials include: - Jean Bernard Lasserre, An Introduction to Polynomial and Semi-Algebraic Optimization, Cambridge University Press, February 2015 - Pablo Parrilo. 6.972 Algebraic Techniques and Semidefinite Optimization. Spring 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, . License: . | ||||
Prerequisites / Notice | Background in Linear and Integer Programming is recommended. |