bibtype C - Conference Paper (international conference)
ARLID 0546760
utime 20220320214454.2
mtime 20211018235959.9
DOI 10.1007/978-3-030-88601-1_12
title (primary) (eng) Entropy-Based Learning of Compositional Models from Data
specification
page_count 10 s.
media_type P
serial
ARLID cav_un_epca*0546759
ISBN 978-3-030-88600-4
ISSN 0302-9743
title Belief Functions: Theory and Applications - 6th International Conference, BELIEF 2021 - Proceedings
page_num 117-126
publisher
place Cham
name Springer
year 2021
editor
name1 Denœux
name2 T.
editor
name1 Lefèvre
name2 E.
editor
name1 Liu
name2 Z.
editor
name1 Pichon
name2 F.
keyword Compositional models
keyword Entropy of Dempster-Shafer belief functions
keyword Decomposable entropy of Dempster-Shafer belief functions
author (primary)
ARLID cav_un_auth*0101118
name1 Jiroušek
name2 Radim
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept (eng) Department of Decision Making Theory
department (cz) MTR
department (eng) MTR
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0216188
name1 Kratochvíl
name2 Václav
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
full_dept Department of Decision Making Theory
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0275452
name1 Shenoy
name2 P. P.
country US
source
url http://library.utia.cas.cz/separaty/2021/MTR/jirousek-0546760.pdf
cas_special
project
project_id GA19-06569S
agency GA ČR
country CZ
ARLID cav_un_auth*0380559
abstract (eng) We investigate learning of belief function compositional models from data using information content and mutual information based on two different definitions of entropy proposed by Jiroušek and Shenoy in 2018 and 2020, respectively. The data consists of 2,310 randomly generated basic assignments of 26 binary variables from a pairwise consistent and decomposable compositional model. We describe results achieved by three simple greedy algorithms for constructing compositional models from the randomly generated low-dimensional basic assignments.
action
ARLID cav_un_auth*0415505
name International Conference on Belief Functions 2021 /6./
dates 20211015
mrcbC20-s 20211019
place Shanghai
country CN
RIV BA
FORD0 10000
FORD1 10100
FORD2 10101
reportyear 2022
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0323760
confidential S
arlyear 2021
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0546759 Belief Functions: Theory and Applications - 6th International Conference, BELIEF 2021 - Proceedings 978-3-030-88600-4 0302-9743 1611-3349 117 126 Cham Springer 2021 1 Lecture Notes in Computer Science 12915
mrcbU67 Denœux T. 340
mrcbU67 Lefèvre E. 340
mrcbU67 Liu Z. 340
mrcbU67 Pichon F. 340