Multi-objective Bayesian Optimization for Neural Architecture Search
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F23%3A00568613" target="_blank" >RIV/67985807:_____/23:00568613 - isvavai.cz</a>
Result on the web
<a href="https://dx.doi.org/10.1007/978-3-031-23492-7_13" target="_blank" >https://dx.doi.org/10.1007/978-3-031-23492-7_13</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-23492-7_13" target="_blank" >10.1007/978-3-031-23492-7_13</a>
Alternative languages
Result language
angličtina
Original language name
Multi-objective Bayesian Optimization for Neural Architecture Search
Original language description
A novel multi-objective algorithm denoted as MO-BayONet is proposed for the Neural Architecture Search (NAS) in this paper. The method based on Bayesian optimization encodes the candidate architectures directly as lists of layers and constructs an extra feature vector for the corresponding surrogate model. The general method allows to accompany the search for the optimal network by additional criteria besides the network performance. The NAS method is applied to combine classification accuracy with network size on two benchmark datasets here. The results indicate that MO-BayONet is able to outperform an available genetic algorithm based approach.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA22-02067S" target="_blank" >GA22-02067S: AppNeCo: Approximate Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence and Soft Computing. 21st International Conference, ICAISC 2022. Proceedings, Part I
ISBN
978-3-031-23491-0
ISSN
0302-9743
e-ISSN
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Number of pages
10
Pages from-to
144-153
Publisher name
Springer
Place of publication
Cham
Event location
Zakopane
Event date
Jun 18, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000972696000013