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Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition
SYS 0380991 LBL 02439^^^^^2200313^^^450 005 20240111140820.1 100 $a 20121101d m y slo 03 ba 101 0-
$a eng $d eng 102 $a ES 200 1-
$a Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition 215 $a 8 s. $c E 463 -1
$1 001 cav_un_epca*0380990 $1 010 $a 978-84-15536-57-4 $1 200 1 $a Proceedings of The Sixth European Workshop on Probabilistic Graphical Models $v S. 355-362 $1 210 $a Granada $c DECSAI, University of Granada $d 2012 610 0-
$a probabilistic graphical models 610 0-
$a probabilistic inference 610 0-
$a CP tensor decomposition 700 -1
$3 cav_un_auth*0101228 $a Vomlel $b Jiří $i Matematická teorie rozhodování $j Department of Decision Making Theory $k MTR $l MTR $p UTIA-B $w Department of Decision Making Theory $4 070 $T Ústav teorie informace a automatizace AV ČR, v. v. i. 701 -1
$3 cav_un_auth*0101212 $a Tichavský $b Petr $i Stochastická informatika $j Department of Stochastic Informatics $k SI $l SI $p UTIA-B $w Department of Stochastic Informatics $4 070 $T Ústav teorie informace a automatizace AV ČR, v. v. i. 856 $q PDF soubor $u http://library.utia.cas.cz/separaty/2012/MTR/vomlel-computationally efficient probabilistic inference with noisy threshold models based on a cp tensor decomposition.pdf $s 570 kB
Number of the records: 1