18.06 Linear Algebra or 18.700 Linear Algebra.
Description
The course will present a thorough introduction to the fundamental algorithmic techniques of Discrete Mathematics  Linear and Convex Programming, Flow & Matching Theory, Randomization, and Approximation. We will tackle a variety of optimization problems by applying these techniques to find efficient algorithms.
Topics include
Format
In addition to 3 hours of lectures each week, students will have regular assignments, and two inclass exams. There will also be a course project which can be either theoretical (e.g. write a report, solve an open problem) or practical (e.g. evaluate an algorithm).
Project
For the course project you will:
Students can work individually or in pairs.
Projects should be set up by the day after session #5.
Grading
