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Publikační činnost
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Record type:
stať ve sborníku (D)
Home Department:
Ústav pro výzkum a aplikace fuzzy modelování (94410)
Title:
Extreme Learning Machine – A New Machine Learning Paradigm
Citace
Perfiljeva, I. Extreme Learning Machine – A New Machine Learning Paradigm.
In:
International Conference on Intelligent and Fuzzy Systems (INFUS 2024): Lecture Notes in Networks and Systems. Vol. 1088 2024-07-16 Canakkale.
Cham: Springer, 2024. s. 7-10. ISBN 978-3-031-70018-7.
Subtitle
Publication year:
2024
Obor:
Number of pages:
4
Page from:
7
Page to:
10
Form of publication:
Elektronická verze
ISBN code:
978-3-031-70018-7
ISSN code:
Proceedings title:
Lecture Notes in Networks and Systems. Vol. 1088
Proceedings:
Mezinárodní
Publisher name:
Springer
Place of publishing:
Cham
Country of Publication:
Sborník vydaný v zahraničí
Název konference:
International Conference on Intelligent and Fuzzy Systems (INFUS 2024)
Conference venue:
Canakkale
Datum zahájení konference:
Typ akce podle státní
příslušnosti účastníků:
Celosvětová akce
WoS code:
001331332200002
EID:
2-s2.0-85203589066
Key words in English:
Extreme Learning Machine; Single Layer Feedforward Neural Network; Activation function
Annotation in original language:
In neural network theory, we analyze two strategies for learning weights: backpropagation and Extreme Learning Machine. The former is common in ANNs with one or more hidden layers, while the latter is becoming popular in ANNs with exactly one hidden layer and weights chosen based on a random selection of the weights and biases of the hidden neurons.
Annotation in english language:
In neural network theory, we analyze two strategies for learning weights: backpropagation and Extreme Learning Machine. The former is common in ANNs with one or more hidden layers, while the latter is becoming popular in ANNs with exactly one hidden layer and weights chosen based on a random selection of the weights and biases of the hidden neurons.
References
Reference
R01:
RIV/61988987:17610/24:A2503A7I
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