Spring 2017

Optimization

Listed in: Mathematics and Statistics, as MATH-294

Moodle site: Course

Faculty

Tanya L. Leise (Section 01)

Description

Optimization is a branch of applied mathematics focused on algorithms to determine maxima and minima of functions, often under constraints. Applications range from economics and finance to machine learning and information retrieval. This course will first develop advanced linear algebra tools, and then will study methods of convex optimization, including linear, quadratic, second-order cone, and semidefinite models. Several applications will be explored, and algorithms will be implemented using mathematical software to aid numerical experimentation.

Requisite:  MATH 211 and either 271 or 272, or permission of the instructor.  Limited to 30 students.  Spring semester.  Professor Leise. 

If Overenrolled: Preference will be given to pre-registered students, math majors, and juniors and seniors.

Cost: 70 ?

Keywords

Quantitative Reasoning

Offerings

2017-18: Not offered
Other years: Offered in Spring 2017