bibtype C - Conference Paper (international conference)
ARLID 0411106
utime 20240103182302.2
mtime 20060210235959.9
ISBN 1-894145-17-8
title (primary) (eng) On approximating multidimensional probability distributions by compositional models
publisher
place Waterloo
name Carleton Scientific
pub_time 2003
specification
page_count 16 s.
serial
title Proceedings of the Third International Symposium on Imprecise Probabilities and Their Applications
page_num 305-320
editor
name1 Bernard
name2 J.-M.
editor
name1 Seidenfeld
name2 T.
editor
name1 Zaffalon
name2 M.
keyword multidimensional distributions
keyword approximations
keyword conditional independence
author (primary)
ARLID cav_un_auth*0101118
name1 Jiroušek
name2 Radim
institution UTIA-B
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI 12A
cas_special
project
project_id IAA2075302
agency GA AV ČR
ARLID cav_un_auth*0001801
research CEZ:AV0Z1075907
abstract (eng) This paper proposes application of compositional models for approximating multidimensional probability distributions with the help of models defined by a reasonable number of parameters. In addition to a theoretical background, a heuristic algorithm solving one part of a model learning process is presented. Its basic idea, construction of an approximation exploiting informational content of given low-dimensional distributions in a maximal possible way, was proposed originally by Albert Perez.
action
ARLID cav_un_auth*0213039
name International Symposium on Imprecise Probabilities and Their Applications /3./
place Lugano
country CH
dates 14.07.2003-17.07.2003
RIV BA
department MTR
permalink http://hdl.handle.net/11104/0131193
ID_orig UTIA-B 20030093
arlyear 2003
mrcbU10 2003
mrcbU10 Waterloo Carleton Scientific
mrcbU12 1-894145-17-8
mrcbU63 Proceedings of the Third International Symposium on Imprecise Probabilities and Their Applications 305 320
mrcbU67 Bernard J.-M. 340
mrcbU67 Seidenfeld T. 340
mrcbU67 Zaffalon M. 340