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A polynomial-time algorithm for learning noisy linear threshold functions

Author
BLUM, A1 ; FRIEZE, A2 ; KANNAN, R1 ; VEMPALA, S1
[1] School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, United States
[2] Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, United States
Issue title
Computational learning theory
Author (monograph)
AUER, P (Author of introductory parts)1 ; MAASS, W (Author of introductory parts)1
[1] Institute for Theoretical Computer Science, Technische Universität Graz, Graz, Austria
Source

Algorithmica. 1998, Vol 22, Num 1-2, pp 35-52 ; ref : 20 ref

ISSN
0178-4617
Scientific domain
Computer science
Publisher
Springer, New York, NY
Publication country
United States
Document type
Article
Language
English
Keyword (fr)
Algorithme apprentissage Apprentissage moteur Complexité temps Fonction seuil Perceptron Réseau neuronal Temps polynomial
Keyword (en)
Learning algorithm Motor learning Time complexity Threshold function Perceptron Neural network Polynomial time
Keyword (es)
Algoritmo aprendizaje Aprendizaje motor Complejidad tiempo Función umbral Perceptron Red neuronal Tiempo polinomial
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02A Theoretical computing / 001D02A05 Algorithmics. Computability. Computer arithmetics

Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C06 Connectionism. Neural networks

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
1655051

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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