| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0431896 |
| utime |
20240111140851.3 |
| mtime |
20141023235959.9 |
| SCOPUS |
84921527707 |
| WOS |
000358253800035 |
| DOI |
10.1007/978-3-319-11433-0_35 |
| title
(primary) (eng) |
An Approximate Tensor-Based Inference Method Applied to the Game of Minesweeper |
| specification |
| page_count |
16 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0431895 |
| ISBN |
978-3-319-11432-3 |
| title
|
Probabilistic Graphical Models |
| part_title |
8745 |
| page_num |
535-550 |
| publisher |
| place |
Cham Heidelberg NewYork Dordrecht London |
| name |
Springer International Publishing |
| year |
2014 |
|
| editor |
| name1 |
van der Gaag |
| name2 |
Linda C. |
|
| editor |
| name1 |
Feelders |
| name2 |
Ad J. |
|
|
| keyword |
Bayesian Networks |
| keyword |
Probabilistic Inference |
| keyword |
CP Tensor Decomposition |
| keyword |
Symmetric Tensor Rank |
| author
(primary) |
| ARLID |
cav_un_auth*0101228 |
| share |
50 |
| name1 |
Vomlel |
| name2 |
Jiří |
| 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 |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101212 |
| share |
50 |
| name1 |
Tichavský |
| name2 |
Petr |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0292670 |
| project_id |
GA13-20012S |
| agency |
GA ČR |
|
| project |
| ARLID |
cav_un_auth*0303443 |
| project_id |
GA14-13713S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
We propose an approximate probabilistic inference method based on the CP-tensor decomposition and apply it to the well known computer game of Minesweeper. In the method we view conditional probability tables of the exactly l-out-of-k functions as tensors and approximate them by a sum of rank-one tensors. The number of the summands is min{l+1,k-l+1}, which is lower than their exact symmetric tensor rank, which is k. Accuracy of the approximation can be tuned by single scalar parameter. The computer game serves as a prototype for applications of inference mechanisms in Bayesian networks, which are not always tractable due to the dimensionality of the problem, but the tensor decomposition may significantly help. |
| action |
| ARLID |
cav_un_auth*0306406 |
| name |
7th European Workshop, PGM 2014, |
| dates |
17.09.2014-19.09.2014 |
| place |
Utrecht |
| country |
NL |
|
| RIV |
IN |
| FORD0 |
10000 |
| FORD1 |
10200 |
| FORD2 |
10201 |
| reportyear |
2015 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0237777 |
| confidential |
S |
| mrcbC83 |
RIV/67985556:_____/14:00431896!RIV15-AV0-67985556 152460049 Doplnění UT WOS a Scopus |
| mrcbC83 |
RIV/67985556:_____/14:00431896!RIV15-GA0-67985556 152501092 Doplnění UT WOS a Scopus |
| arlyear |
2014 |
| mrcbU14 |
84921527707 SCOPUS |
| mrcbU34 |
000358253800035 WOS |
| mrcbU56 |
PDF soubor 431 kB |
| mrcbU63 |
cav_un_epca*0431895 Probabilistic Graphical Models 978-3-319-11432-3 535 550 Cham Heidelberg NewYork Dordrecht London Springer International Publishing 2014 Lecture Notes in Computer Science 8745 |
| mrcbU67 |
van der Gaag Linda C. 340 |
| mrcbU67 |
Feelders Ad J. 340 |
|