Training products of experts by minimizing contrastive divergence
- Author
- HINTON, Geoffrey E1
[1] Gatsby Computational Neuroscience Unit, University College London, London WC1N 3AR, United Kingdom - Source
Neural computation. 2002, Vol 14, Num 8, pp 1771-1800 ; ref : 1 p.1/4
- ISSN
- 0899-7667
- Scientific domain
- Computer science; Neurology; Psychology, psychopathology, psychiatry
- Publisher
- MIT Press, Cambridge, MA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Keyword (fr)
- Algorithme apprentissage Dérivée fonction Echantillon Fonction objectif Fonction partition Loi probabilité Sous produit Type donnée Produit expert
- Keyword (en)
- Learning algorithm Function derivative Sample Objective function Partition function Probability distribution By product Data type
- Keyword (es)
- Algoritmo aprendizaje Derivada función Muestra Función objetivo Función partición Ley probabilidad Subproducto Tipo dato
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C02 Learning and adaptive systems
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 13750475
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
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DOI
10.1162/089976602760128018 
https://dx.doi.org/10.1162/089976602760128018
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