UBAL: a Universal Bidirectional Activation-based Learning Rule for Neural Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337712" target="_blank" >RIV/68407700:21730/19:00337712 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/abs/10.1145/3372422.3372443" target="_blank" >https://dl.acm.org/doi/abs/10.1145/3372422.3372443</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3372422.3372443" target="_blank" >10.1145/3372422.3372443</a>

Result language
angličtina
Original language name
UBAL: a Universal Bidirectional Activation-based Learning Rule for Neural Networks
Original language description
Artificial neural networks, in particular the deep end-to-end architectures trained by error backpropagation (BP), are currently the topmost used learning systems. However, learning in such systems is only loosely inspired by the actual neural mechanisms. Algorithms based on local activation differences were designed as a biologically plausible alternative to BP. We propose Universal Bidirectional Activation-based Learning, a novel neural model which enhances the contrastive Hebbian learning rule with special hyperparameters yielding a single learning rule that can perform multiple ways of learning, similarly to what is assumed about learning in the brain. Unlike others, our model consists of mutually dependent, yet separate weight matrices for different directions of activation propagation. We show that UBAL can learn different tasks (such as pattern retrieval, denoising, or classification) with different setups of the learning hyperparameters. We also demonstrate the performance of our algorithm on a machine learning benchmark (MNIST). The experimental results presented in this paper confirm that UBAL is comparable with a basic version BP-trained multilayer network and the related biologically-motivated models.
Czech name
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Czech description
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Project
<a href="/en/project/VI20172019082" target="_blank" >VI20172019082: Smart Camera - New Generation Monitoring Centre</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2019 International Conference on Computational Intelligence and Intelligent Systems
ISBN
978-1-4503-7259-6
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
57-62
Publisher name
Association for Computing Machinery
Place of publication
New York
Event location
Bangkok
Event date
Nov 23, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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