English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Cooperative Cuts: Graph Cuts with Submodular Edge Weights

Jegelka, S., & Bilmes, J.(2010). Cooperative Cuts: Graph Cuts with Submodular Edge Weights (189). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

Item is

Files

show Files
hide Files
:
subcutsShort_6330[0].pdf (Publisher version), 456KB
Name:
subcutsShort_6330[0].pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Jegelka, S1, 2, Author              
Bilmes, J, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: We introduce a problem we call Cooperative cut, where the goal is to find a minimum-cost graph cut but where a submodular function is used to define the cost of a subsets of edges. That means, the cost of an edge that is added to the current cut set C depends on the edges in C. This generalization of the cost in the standard min-cut problem to a submodular cost function immediately makes the problem harder. Not only do we prove NP hardness even for nonnegative submodular costs, but also show a lower bound of Omega(|V|^(1/3)) on the approximation factor for the problem. On the positive side, we propose and compare four approximation algorithms with an overall approximation factor of min |V|/2, |C*|, O( sqrt(|E|) log |V|), |P_max|, where C* is the optimal solution, and P_max is the longest s, t path across the cut between given s, t. We also introduce additional heuristics for the problem which have attractive properties from the perspective of practical applications and implementations in that existing fast min-cut libraries may be used as subroutines. Both our approximation algorithms, and our heuristics, appear to do well in practice.

Details

show
hide
Language(s):
 Dates: 2010-03
 Publication Status: Published in print
 Pages: 32
 Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics
 Table of Contents: -
 Rev. Type: -
 Identifiers: Report Nr.: 189
BibTex Citekey: 6330
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Technical Report of the Max Planck Institute for Biological Cybernetics
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 189 Sequence Number: - Start / End Page: - Identifier: -