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pro vyhledávání: '"Kyriakides, George"'
In this work, we propose a novel evolutionary algorithm for neural architecture search, applicable to global search spaces. The algorithm's architectural representation organizes the topology in multiple hierarchical modules, while the design process
Externí odkaz:
http://arxiv.org/abs/2107.08484
Neural Architecture Search (NAS) is a research field concerned with utilizing optimization algorithms to design optimal neural network architectures. There are many approaches concerning the architectural search spaces, optimization algorithms, as we
Externí odkaz:
http://arxiv.org/abs/2005.11074
NORD (Neural Operations Research & Development) is an open source distributed deep learning architectural research framework, based on PyTorch, MPI and Horovod. It aims to make research of deep architectures easier for experts of different domains, i
Externí odkaz:
http://arxiv.org/abs/1810.08648
Autor:
Kyriakides, George1 (AUTHOR) ge.kyriakides@uom.edu.gr, Margaritis, Konstantinos1 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Jan2022, Vol. 34 Issue 2, p899-909. 11p.
Autor:
Kyriakides, George1 (AUTHOR) ge.kyriakides@uom.edu.gr, Margaritis, Konstantinos1 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Dec2020, Vol. 32 Issue 23, p17321-17332. 12p.
Publikováno v:
Artificial Intelligence Applications and Innovations
Neural Architecture Search is becoming an increasingly popular research field and method to design deep learning architectures. Most research focuses on searching for small blocks of deep learning operations, or micro-search. This method yields satis
Akademický článek
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Publikováno v:
In Software Impacts November 2020 6
Publikováno v:
ACM International Conference Proceeding Series; 11/29/2018, p113-116, 4p