---
res:
  bibo_abstract:
  - We  propose  a  general  dual  ascent  framework  for  Lagrangean decomposition
    of combinatorial problems.  Although methods of this type have shown their efficiency
    for a number of problems, so far there was no general algorithm applicable to
    multiple problem types. In this work, we propose such a general algorithm. It
    depends on several parameters, which can be used to optimize its performance in
    each particular setting. We demonstrate efficacy of our method on graph matching
    and multicut problems, where it outperforms state-of-the-art solvers including
    those based on subgradient optimization and off-the-shelf linear programming solvers.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Paul
      foaf_name: Swoboda, Paul
      foaf_surname: Swoboda
      foaf_workInfoHomepage: http://www.librecat.org/personId=446560C6-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Jan
      foaf_name: Kuske, Jan
      foaf_surname: Kuske
  - foaf_Person:
      foaf_givenName: Bogdan
      foaf_name: Savchynskyy, Bogdan
      foaf_surname: Savchynskyy
  bibo_doi: 10.1109/CVPR.2017.526
  bibo_volume: 2017
  dct_date: 2017^xs_gYear
  dct_identifier:
  - UT:000418371405005
  dct_isPartOf:
  - http://id.crossref.org/issn/978-153860457-1
  dct_language: eng
  dct_publisher: IEEE@
  dct_title: A dual ascent framework for Lagrangean decomposition of combinatorial
    problems@
...