Approximation Algorithms Part II

Name: Approximation Algorithms Part II
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Author: École normale supérieure

课程

英语

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来自www.coursera.org

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4 序列
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课程详情

教学大纲

Week 1 - Linear Programming Duality
This module does not study any specific combinatorial optimization problem. Instead, it introduces a central feature of linear programming, duality.
Week 2 - Steiner Forest and Primal-Dual Approximation Algorithms
This module uses linear programming duality to design an algorithm for another basic problem, the Steiner forest problem.
Week 3 - Facility Location and Primal-Dual Approximation Algorithms
This module continues teaching algorithmic applications of linear programming duality by applying it to another basic problem, the facility location problem.
Week 4 - Maximum Cut and Semi-Definite Programming
We introduce a generalization of linear programming, semi-definite programming.This module uses semi-definite programming to design an approximation algorithm for another basic problem, the maximum cut problem.

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讲师

Claire Mathieu

编辑

L’École normale supérieure (ENS) est un établissement d'enseignement supérieur pour les études prédoctorales et doctorales (graduate school) et un haut lieu de la recherche française. L'ENS offre à 300 nouveaux étudiants et 200 doctorants chaque année une formation de haut niveau, largement pluridisciplinaire, des humanités et sciences sociales aux sciences dures. Régulièrement distinguée au niveau international, l'ENS a formé 10 médailles Fields et 13 prix Nobel.