bibtype V - Research Report
ARLID 0377918
utime 20240103201011.3
mtime 20120828235959.9
title (primary) (eng) LP relaxations and pruning for characteristic imsets
publisher
place Praha
name ÚTIA AVČR
pub_time 2012
specification
page_count 30 s.
edition
name Research Report
volume_id 2323
keyword learning Bayesian network structure
keyword quality criterion
keyword integer linear programming
author (primary)
ARLID cav_un_auth*0101202
name1 Studený
name2 Milan
full_dept (cz) Matematická teorie rozhodování
full_dept (eng) Department of Decision Making Theory
department (cz) MTR
department (eng) MTR
institution UTIA-B
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2012/MTR/Studeny-LP relaxations and pruning for characteristic imsets.pdf
cas_special
project
project_id GA201/08/0539
agency GA ČR
ARLID cav_un_auth*0239648
abstract (eng) The geometric approach to learning BN structure is to represent it by a certain vector; a suitable such zero-one vector is the characteristic imset, which allows to reformulate the task of finding global maximum of a score over BN structures as an integer linear programming problem. The main contribution of this report is an LP relaxation of the corresponding polytope, that is, a polyhedral description of the domain of the respective integer linear programming problem.
reportyear 2013
RIV BA
num_of_auth 1
mrcbC52 4 O 4o 20231122135116.2
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0209940
arlyear 2012
mrcbTft \nSoubory v repozitáři: 0377918.pdf
mrcbU10 2012
mrcbU10 Praha ÚTIA AVČR