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学生对 École normale supérieure 提供的 Approximation Algorithms Part I 的评价和反馈

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课程概述

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....

热门审阅

AK

Apr 16, 2016

A really good course for programmers who want to take a bit deeper into CS.

MG

Oct 25, 2021

Excellent Course Really helped me to have an in depth knowledge in every concept

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51 - Approximation Algorithms Part I 的 75 个评论（共 110 个）

创建者 Kaustubh M

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Oct 17, 2021

awesome

创建者 Ajay S

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Sep 9, 2024

super

创建者 Karthikeya G

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Sep 16, 2022

good

创建者 Siddu R

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Oct 21, 2021

noice

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Oct 13, 2021

ossum

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Oct 6, 2021

nice

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Jun 18, 2024

nice

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Apr 4, 2023

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Mar 5, 2023

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Feb 21, 2023

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创建者 ASADUR Z N

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Oct 4, 2022

hyh

创建者 Yuvaraj G

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Sep 22, 2022

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Nov 9, 2021

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Nov 2, 2021

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Oct 31, 2021

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Oct 31, 2021

GOOD

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Oct 31, 2021

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Oct 29, 2021

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Oct 28, 2021

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Oct 27, 2021

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Oct 26, 2021

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Oct 23, 2021

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Oct 23, 2021

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Oct 21, 2021

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Oct 14, 2021

Good