Efficient learning of hierarchical latent class models

Author

ZHANG, Nevin L¹ ; KOCKA, Tomao²
[1] Department of Computer Science. Hong Kong University of Science & Technology, Hong-Kong
[2] Laboratory of Intelligent Systems Prague Prague University of Economics, Prague, Czech Republic

Conference title

16th IEEE international conference on tools with artificial intelligence ICTAI 2004 (Boca Raton Fl, 15-17 November 2004)

Conference name

ICTAI : international conference on tools with artificial intelligence (16 ; Boca Raton FL 2004)

Source

Proceedings - International Conference on Tools with Artificial Intelligence, TAI. 2004 ; 1Vol, pp 585-593, 9 p ; ref : 8 ref

ISSN

1082-3409

ISBN

0-7695-2236-X

Scientific domain

Computer science

Publisher

IEEE, Los Alamitos CA

Publication country

United States

Document type

Conference Paper

Language

English

Keyword (fr)

Algorithme recherche Complexité calcul Extensibilité Intelligence artificielle Modèle donnée Modélisation Réseau Bayes Structure arborescente Système hiérarchisé

Keyword (en)

Search algorithm Computational complexity Scalability Artificial intelligence Data models Modeling Bayes network Tree structure Hierarchical system

Keyword (es)

Algoritmo búsqueda Complejidad computación Estensibilidad Inteligencia artificial Modelización Red Bayes Estructura arborescente Sistema jerarquizado

Classification

Pascal

001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence

Discipline

Computer science : theoretical automation and systems

Origin

Inist-CNRS

Database

PASCAL

INIST identifier

19103888

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS