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Optimizing the Structures of Transformer Neural Networks Using Parallel Simulated Annealing Cover

Optimizing the Structures of Transformer Neural Networks Using Parallel Simulated Annealing

Journal of Artificial Intelligence and Soft Computing Research
Volume 14 (2024): Issue 3 (June 2024)
By: Maciej Trzciński,  Szymon Łukasik and  Amir H. Gandomi  
Open Access
|Jun 2024

Authors

Maciej Trzciński

AGH University of Krakow, Faculty of Physics and Applied Computer Science, Poland
NASK National Research Institute, Warsaw, Poland

Szymon Łukasik

slukasik@agh.edu.pl

AGH University of Krakow, Faculty of Physics and Applied Computer Science, Poland
NASK National Research Institute, Warsaw, Poland
Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Amir H. Gandomi

University of Technology Sydney, Faculty of Engineering and Information Technology, Australia
University Research and Innovation Center (EKIK), Óbuda University, Budapest, Hungary
DOI: https://doi.org/10.2478/jaiscr-2024-0015
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Language: English
Page range: 267 - 282
Submitted on: Jan 9, 2024
|
Accepted on: May 26, 2024
|
Published on: Jun 11, 2024
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
neural architecture search,
transformers,
natural language processing,
simulated annealing
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2024 Maciej Trzciński, Szymon Łukasik, Amir H. Gandomi, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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