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Seminar on Internet Technologies (Summer 2020): Difference between revisions
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Seminar on Internet Technologies (Summer 2020) (view source)
Revision as of 15:21, 28 April 2020
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| Learning Combinatorial Optimization Algorithms over Graphs | | Learning Combinatorial Optimization Algorithms over Graphs | ||
| There are many NP-hard problems about graph. However, these NP-hard problems cannot be soloved fast by optimization solver. Approximation algorithms could solve them fast in the cost of sacrificing the accuracy. Recently, some algorithms based on machine learning have been proposed to solve these NP-hard problems in the manner of end-to-end. After reproducing one classical paper, the student is required to find solution for a new assignment problem | | There are many NP-hard problems about graph. However, these NP-hard problems cannot be soloved fast by optimization solver. Approximation algorithms could solve them fast in the cost of sacrificing the accuracy. Recently, some algorithms based on machine learning have been proposed to solve these NP-hard problems in the manner of end-to-end. After reproducing one classical paper, the student is required to find solution for a new assignment problem | ||
| The student should be familiar with machine learning and Integer linear programming | | The student should be familiar with machine learning and Integer linear programming | ||
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| [https://www.microsoft.com/en-us/research/wp-content/uploads/2017/08/Bahl-MobiCom-2015.pdf] | | [https://www.microsoft.com/en-us/research/wp-content/uploads/2017/08/Bahl-MobiCom-2015.pdf] | ||
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| Learning Combinatorial Optimization Algorithms over Graphs | | Learning Combinatorial Optimization Algorithms over Graphs (Ismot Jerin) | ||
| There are many NP-hard problems about graph. However, these NP-hard problems cannot be solved fast by optimization solver. Approximation algorithms could solve them fast in the cost of sacrificing the accuracy. Recently, some algorithms based on machine learning have been proposed to solve these NP-hard problems in the manner of end-to-end. After reproducing one classical paper, the student is required to find solution for a new Vihecl Routing Problem. | | There are many NP-hard problems about graph. However, these NP-hard problems cannot be solved fast by optimization solver. Approximation algorithms could solve them fast in the cost of sacrificing the accuracy. Recently, some algorithms based on machine learning have been proposed to solve these NP-hard problems in the manner of end-to-end. After reproducing one classical paper, the student is required to find solution for a new Vihecl Routing Problem. | ||
| The student should be familiar with TSP, Matching, and Integer linear programming | | The student should be familiar with TSP, Matching, and Integer linear programming | ||