| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0573617 |
| utime |
20240402214146.9 |
| mtime |
20230717235959.9 |
| SCOPUS |
85172915895 |
| title
(primary) (eng) |
On the relationship between graphical and compositional models for the Dempster-Shafer theory of belief functions |
| specification |
| page_count |
11 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0576278 |
| ISSN |
Proceedings of Machine Learning Research, Volume 215: International Symposium on Imprecise Probability: Theories and Applications, |
| title
|
Proceedings of Machine Learning Research, Volume 215: International Symposium on Imprecise Probability: Theories and Applications, |
| page_num |
259-269 |
| publisher |
| place |
Almerı́a |
| name |
PMLR |
| year |
2023 |
|
|
| keyword |
joint belief functions |
| keyword |
conditional independence |
| keyword |
Markov models |
| keyword |
composition operators |
| keyword |
Dempster’s combination rule |
| keyword |
conditionals |
| 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 |
|
| cas_special |
| project |
| project_id |
GA21-07494S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0430801 |
|
| abstract
(eng) |
This paper studies the relationship between graphical and compositional models representing joint belief functions. In probability theory, the class of Bayesian networks (directed graphical models) is equivalent to compositional models. Such an equivalence does not hold for the Dempster-Shafer belief function theory. We show that each directed graphical belief function model can be represented as a compositional model, but the converse does not hold. As there are two composition operators for belief functions, there are two types of compositional models. In studying their relation to graphical models, they are closely connected. Namely, one is more specific than the other. A precise relationship between these two composition operators is described. |
| action |
| ARLID |
cav_un_auth*0452244 |
| name |
International Symposium on Imprecise Probability: Theories and Applications 2023 /13./ |
| dates |
20230711 |
| mrcbC20-s |
20230714 |
| place |
Oviedo |
| country |
ES |
|
| RIV |
BA |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10101 |
| reportyear |
2024 |
| num_of_auth |
3 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0345846 |
| confidential |
S |
| arlyear |
2023 |
| mrcbU14 |
85172915895 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0576278 Proceedings of Machine Learning Research, Volume 215: International Symposium on Imprecise Probability: Theories and Applications, PMLR 2023 Almerı́a 259 269 2640-3498 |
|