Get started with custom lists to organize and share courses.

Sign up

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Approximation Algorithms Part II

École normale supérieure via Coursera

  • Provider Coursera
  • Subject Algorithms and Data Structures
  • Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Start Date
  • Duration 4 weeks long
  • Learn more about MOOCs

Taken this course? Share your experience with other students. Write review

Overview

Sign up to Coursera courses for free Learn how

Approximation algorithms, Part 2

This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut.

By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques. Upon completion, you will be able to recognize, when faced with a new combinatorial optimization problem, whether it is close to one of a few known basic problems, and will be able to design linear programming relaxations and use randomized rounding to attempt to solve your own problem. The course content and in particular the homework is of a theoretical nature without any programming assignments.

This is the second of a two-part course on Approximation Algorithms.

Taught by

Claire Mathieu

Help Center

Most commonly asked questions about Coursera Coursera

Reviews for Coursera's Approximation Algorithms Part II
Based on 0 reviews

  • 5 star 0%
  • 4 star 0%
  • 3 star 0%
  • 2 star 0%
  • 1 star 0%

Did you take this course? Share your experience with other students.

Write a review

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.