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Discrete graphical models: an optimization perspective

This monograph is about discrete energy minimization for discrete graphical models. It considers graphical models, or, more precisely, maximum a posteriori inference for graphical models, purely as a combinatorial optimization problem.

Detalles Bibliográficos
Autor principal: Savchynskyy, Bogdan
Lenguaje:eng
Publicado: Now Publishers 2019
Materias:
XX
Acceso en línea:http://cds.cern.ch/record/2760365
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author Savchynskyy, Bogdan
author_facet Savchynskyy, Bogdan
author_sort Savchynskyy, Bogdan
collection CERN
description This monograph is about discrete energy minimization for discrete graphical models. It considers graphical models, or, more precisely, maximum a posteriori inference for graphical models, purely as a combinatorial optimization problem.
id cern-2760365
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
publisher Now Publishers
record_format invenio
spelling cern-27603652021-04-21T16:40:15Zhttp://cds.cern.ch/record/2760365engSavchynskyy, BogdanDiscrete graphical models: an optimization perspectiveXXThis monograph is about discrete energy minimization for discrete graphical models. It considers graphical models, or, more precisely, maximum a posteriori inference for graphical models, purely as a combinatorial optimization problem.Now Publishersoai:cds.cern.ch:27603652019
spellingShingle XX
Savchynskyy, Bogdan
Discrete graphical models: an optimization perspective
title Discrete graphical models: an optimization perspective
title_full Discrete graphical models: an optimization perspective
title_fullStr Discrete graphical models: an optimization perspective
title_full_unstemmed Discrete graphical models: an optimization perspective
title_short Discrete graphical models: an optimization perspective
title_sort discrete graphical models: an optimization perspective
topic XX
url http://cds.cern.ch/record/2760365
work_keys_str_mv AT savchynskyybogdan discretegraphicalmodelsanoptimizationperspective