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Neural Computing and Applications
Published in: Neural Computing and Applications 11/2020

03-04-2020 | Editorial

Brain-inspired computing and machine learning

Authors: Lazaros S. Iliadis, Vera Kurkova, Barbara Hammer

Published in: Neural Computing and Applications | Issue 11/2020

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Excerpt

Recent research in machine learning (ML) and neurophysiology has focused in the development of highly intelligent algorithms, utilizing information processing principles of the human brain. Deep learning is inspired by the architecture of the cerebral cortex and it has attracted the attention of many artificial intelligence (AI) scientists. It is the dominating AI approach in specific domains (e.g., image–voice classification, object detection) regardless of its requirements in high computational power and in high volume of data. …
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Literature
1.
Livieris IE, Pintelas P (2013) A new conjugate gradient algorithm for training neural networks based on a modified secant equation. Appl Math Comput 221:491–502MathSciNetMATH
2.
Boukis C, Mandic DP, Constantinides AG, Polymerakos L (2010) A modified Armijo rule for the online selection of learning rate of the LMS algorithm. Digit Signal Process 20(3):630–639
Metadata
Title
Brain-inspired computing and machine learning
Authors
Lazaros S. Iliadis
Vera Kurkova
Barbara Hammer
Publication date
03-04-2020
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 11/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-04888-6

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