Back to Approximation Algorithms Part I
Learner Reviews & Feedback for Approximation Algorithms Part I by École normale supérieure
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About the Course
Approximation algorithms, Part I
How efficiently can you pack objects into a minimum number of boxes? How well can you cluster nodes so as to cheaply separate a network into components around a few centers? These are examples of NP-hard combinatorial optimization problems. It is most likely impossible to solve such problems efficiently, so our aim is to give an approximate solution that can be computed in polynomial time and that at the same time has provable guarantees on its cost relative to the optimum.
This course assumes knowledge of a standard undergraduate Algorithms course, and particularly emphasizes algorithms that can be designed using linear programming, a favorite and amazingly successful technique in this area. By taking 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 first of a two-part course on Approximation Algorithms.
Top reviews
DA
Jan 26, 2016
The course provides a high-level introduction to approximation algorithm. There is no programming assignments but it provides nice introduction to approximation algorithm.
MH
May 28, 2020
A great course if you want to learn about approximation algorithms from the point of view of linear programming relaxation!
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101 - 110 of 110 Reviews for Approximation Algorithms Part I
By ALAPATI N V S
•Sep 30, 2021
very good
By Kilari H C
•Feb 23, 2022
good
By Katuri B
•Oct 28, 2021
good
By SRAVYA C V
•Oct 9, 2021
Good
By Shaik N K
•Sep 30, 2021
GOOD
By PAIDIPATI H V
•Sep 3, 2022
ok
By Somanth R
•Oct 21, 2021
NA
By Achyutha P
•Sep 28, 2022
good
By Susanne W
•Jan 9, 2017
-
By Nookala S H
•Oct 27, 2021
GOOD