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Voltar para Approximation Algorithms Part I

Comentários e feedback de alunos de Approximation Algorithms Part I da instituição Escola Normal Superior de Paris

474 classificações
95 avaliações

Sobre o curso

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....

Melhores avaliações


26 de jan de 2016

The course provides a high-level introduction to approximation algorithm. There is no programming assignments but it provides nice introduction to approximation algorithm.


28 de mai de 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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76 — 94 de 94 Avaliações para o Approximation Algorithms Part I

por Claus D M P

4 de ago de 2016

Lectures and content were great. The theme of the course is to provide insight into the approaches used to investigate approximation algorithms for NP hard problems and the theoretical techniques used to assess the effectiveness of the approximation algorithm against the best answer. The production quality of the lecture videos and slides was high.

The content of the quizzes and assignments was mostly appropriate and well organized. However, the authors appeared to struggle with the platform. At times there were comments such as, you need to enter something in the box but it was not actually being used. Answers to the assignments required using substantial mathematical notation, but LaTex was not enabled in the discussion or text entry boxes (no longer available in the Coursera platform??) so the work around was to upload answers to a bunch of questions as a single PDF document. Flow of the individual modules (lectures, slides, quizzes) was inconsistent, varying from week to week.

por victor g

21 de jul de 2017

A very synthetic course on the topic.Explanations are of great quality and elegant!

Every algorithms given are analysed on a mathematical point of view.

ENS should enable people to get certificate for this course ! I would prefer

give money to this top institution in theorical science than to the huge private universities

To improve : the commitment of the staff to the forum

por Abhijit O

21 de out de 2016

Content of the course is great. However , at time assignments are very difficult to understand. There are probably very few students who take this course at any time , so you dont get much help from forums. TA's and Professor as well have not responded to any of our questions. I dont expect any course to be cakewalk but at least some help need to be provided.

por Mingda Q

21 de fev de 2016

Lectures are well-organized. Some assignments (e.g., Assignment 3, which involves merely understanding an algorithm, rather than proving correctness and approx. ratio) are extraordinarily stupid and somewhat tangential.

por Vivek A

19 de jan de 2016

This course is quite advanced and the assignments require prerequisite skills to prove time complexity etc. If you are upto it, then for sure take this course. The instructor is quite thorough.

por Peter U

1 de jun de 2017

The content of the course is good and the lectures even better. However the quizzes and homeworks could use an update or refresh. The forums connected to the course is a ghosttown.

por Philippe S

7 de ago de 2016

Very interesting, explanations are clear and easy to understand

por maturi p

30 de set de 2021

it is a very good course

por sai v k

25 de out de 2021

Good for learning

por Janardhan G

29 de out de 2021

good to learn.


30 de set de 2021

very good

por Kilari H C

23 de fev de 2022



28 de out de 2021



9 de out de 2021


por Shaik N K

30 de set de 2021


por Somanth R

21 de out de 2021


por Susanne W

9 de jan de 2017


por Ricardo M C

2 de jun de 2016

This course covers the basic ground about approximation algorithms and would be very valuable for a practitioner, but seems designed for people who already know the materials and is more theoretical than applied.

Lectures are very abstract --with a description of the problem and a formal description of the solution--, there are few examples with step-by-step tracing of algorithms --that is how the algorithm actually works to solve the problem--, and a significant amount of expertise is assumed --so much so, that you wouldn't need this course. For example, there are questions about "approximation ratio", but it is not explained. This seems like something that is inherent to approximation algorithms, but is only asked in the exams/project, and is not even mentioned in the lectures. Similar issues abound around the course.

por Nookala S

27 de out de 2021