Coursera – Approximation Algorithms Part II 2022-12

Approximation Algorithms Part II course published by Coursera Online University. This is a continuation of the Approximate Algorithms of Part 1. Here you will learn the duality of linear programming applied in designing some approximate algorithms and semi-definite programming applied in Maxcut.

By completing the two parts of this course, you will encounter a wide range of problems in the fundamentals of theoretical computer science and 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 the few well-known fundamental problems, and you will be able to find linear programming relaxations. and use random rounding to try to solve your own. The problem of the course content and especially the course assignments is theoretical in nature and without programming assignments.

This is the second of a two-part course on approximate algorithms.

What you will learn in Approximation Algorithms Part II:

• Duality of linear programming
• Steiner forest and primal-dual approximation algorithms
• Facility location and primal-dual approximation algorithms
• Maximum cutting and semi-definite programming

Course Specifications

• Publisher: Coursera
• Instructors: Claire Mathieu
• Language: English
• Level: Introductory to Advanced
• institution/university: École normale supérieure
• Number of Weeks: 4
• Duration: Approx. 33 hours to complete

Courses included:

Week 1

Linear Programming Duality

Week 2

Steiner Forest and Primal-Dual Approximation Algorithms

Week 3

Facility Location and Primal-Dual Approximation Algorithms

Week 4

Maximum Cut and Semi-Definite Programming

Pictures

Approximation Algorithms Part II Introduction Video

Installation Guide

After Extract, watch with your favorite Player.

Subtitle: English

Quality: 720p

Download Link

Download Part 1 – 1 GB

Download Part 2 – 475 MB

Size

1.47 GB