| bibtype |
J -
Journal Article
|
| ARLID |
0353652 |
| utime |
20250303095124.5 |
| mtime |
20110107235959.9 |
| WOS |
000286637200006 |
| title
(primary) (eng) |
Efficient algorithms for conditional independence inference |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0255947 |
| ISSN |
1532-4435 |
| title
|
Journal of Machine Learning Research |
| volume_id |
11 |
| volume |
1 (2010) |
| page_num |
3453-3479 |
| publisher |
|
|
| keyword |
conditional independence inference |
| keyword |
linear programming approach |
| author
(primary) |
| ARLID |
cav_un_auth*0268027 |
| name1 |
Bouckaert |
| name2 |
R. |
| country |
NZ |
|
| author
|
| ARLID |
cav_un_auth*0261765 |
| name1 |
Hemmecke |
| name2 |
R. |
| country |
DE |
|
| author
|
| ARLID |
cav_un_auth*0268009 |
| name1 |
Lindner |
| name2 |
S. |
| country |
DE |
|
| author
|
| ARLID |
cav_un_auth*0101202 |
| name1 |
Studený |
| name2 |
Milan |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| institution |
UTIA-B |
| full_dept |
Department of Decision Making Theory |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA201/08/0539 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239648 |
|
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transform CI statements into certain integral vectors and to verify by a computer the corresponding algebraic relation between the vectors, called the independence implication. The main contribution of the paper is a new method, based on linear programming (LP), which overcomes the limitation of former methods to the number of involved variables. The computational experiments, described in the paper, also show that the new method is faster than the previous ones. |
| reportyear |
2011 |
| RIV |
BA |
| permalink |
http://hdl.handle.net/11104/0192831 |
| mrcbT16-e |
AUTOMATIONCONTROLSYSTEMS|COMPUTERSCIENCEARTIFICIALINTELLIGENCE |
| mrcbT16-f |
4.967 |
| mrcbT16-g |
0.456 |
| mrcbT16-h |
6.1 |
| mrcbT16-i |
0.02175 |
| mrcbT16-j |
2.448 |
| mrcbT16-k |
4766 |
| mrcbT16-l |
114 |
| mrcbT16-s |
1.282 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
96.556 |
| mrcbT16-C |
95.278 |
| mrcbT16-D |
Q1* |
| mrcbT16-E |
Q1 |
| arlyear |
2010 |
| mrcbU34 |
000286637200006 WOS |
| mrcbU63 |
cav_un_epca*0255947 Journal of Machine Learning Research 1532-4435 Roč. 11 č. 1 2010 3453 3479 Microtome Publ |
|