Description
Course on Approximation Algorithms Part II, published by Coursera Online University. This is a continuation of Approximate algorithms from part 1Here you will learn the duality of linear programming applied to the design of some approximate algorithms and semi-definite programming applied in Maxcut.
By completing both parts of this course, you will encounter a wide range of problems related to the fundamentals of theoretical computer science and powerful design and analysis techniques. Once completed, 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 relaxations in linear programming. and use random rounding to try to solve yours. The problem with 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 Part II of Approximation Algorithms:
- Duality of linear programming
- Steiner forest and primal-double approximation algorithms
- Facility location and primal-double approximation algorithms
- Maximum cut and semi-defined programming
Course Specifications
- Editor: Coursera
- Instructors: Claire Mathieu
- French language
- Level: Introductory to Advanced
- establishment/university: École Normale Supérieure
- Number of weeks: 4
- Duration: approx. 33 hours to complete
Courses included:
Week 1
Duality of linear programming
Week 2
Steiner forest and primal-double approximation algorithms
Week 3
Facility location and primal-double approximation algorithms
Week 4
Maximum cut and semi-defined programming
Pictures
Intro to Approximation Algorithms Part II Video
Installation guide
After the clip, watch with your favorite reader.
Subtitle: English
Quality: 720p
Download link
File password(s): free download software
size
1.47 GB