The Minimum Cut Problem: Difference between revisions

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=Internal=
=Internal=
* [[Graph_Concepts#The_Minimum_Cut_Problem|Graph Concepts]]
* [[Graph_Concepts#The_Minimum_Cut_Problem|Graph Concepts]]
=Overview=
Given an undirected graph G = (V, E), compute a cut with the fewest number of crossing edges.
Applications:
* identify network bottleneck or weaknesses
* community detection in social networks
* image segmentation
=Algorithms=
==Karger's Contraction Algorithm==
Karger's Contraction Algorithm is an example of a [[Randomized_Algorithms#Overview|randomized algorithm]].
{{Internal|Karger%27s_Contraction_Algorithm#Overview|Karger's Contraction Algorithm}}

Latest revision as of 22:53, 20 October 2021

Internal

Overview

Given an undirected graph G = (V, E), compute a cut with the fewest number of crossing edges.

Applications:

  • identify network bottleneck or weaknesses
  • community detection in social networks
  • image segmentation

Algorithms

Karger's Contraction Algorithm

Karger's Contraction Algorithm is an example of a randomized algorithm.

Karger's Contraction Algorithm