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Approximation Algorithms Part II

Approximation algorithms, Part 2 This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of 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 second of a two-part course on Approximation Algorithms.

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状态:Advanced Mathematics
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AP

5.0评论日期:Oct 27, 2016

Demanding course with lots of great algorithm concepts based on Linear Programming.

RA

5.0评论日期:Mar 13, 2016

It is remarkable to note that Professor Claire Mathieu explains such a complex subject in such a elegant and understandable manner.

PV

5.0评论日期:Feb 15, 2017

Even better than the first! Very good classes (except for the two first of week 3 ...)

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Andrew Panufnik
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评论日期:Oct 28, 2016
Deleted Account
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Claus D. Makowka, PhD
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评论日期:Aug 18, 2016
Maxime Jaubert
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评论日期:Feb 26, 2017
Zhouningnan
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评论日期:Jan 10, 2017
Refik Arkut
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评论日期:Mar 14, 2016
Paulo Emílio de Vilhena
5.0
评论日期:Feb 16, 2017
Reynaldo Gil-Pons
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评论日期:Mar 4, 2016
victor guillot
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评论日期:Jul 21, 2017