Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders

Piotr Kaszuba; Maciej Komosinski; Agnieszka Mensfelt

doi:10.1109/CEC45853.2021.9504910

Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders

Piotr Kaszuba, Maciej Komosinski, Agnieszka Mensfelt

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1123-1130
Number of pages	8
ISBN (Electronic)	9781728183923
DOIs	https://doi.org/10.1109/CEC45853.2021.9504910
Publication status	Published - 9 Aug 2021
Event	2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Virtual, Krakow, Poland Duration: 28 Jun 2021 → 1 Jul 2021

Conference

Conference	2021 IEEE Congress on Evolutionary Computation, CEC 2021
Country/Territory	Poland
City	Virtual, Krakow
Period	28/06/21 → 1/07/21

Keywords

Autoencoder
Evolutionary design
Fitness landscape
Genetic representation
Latent representation

Access to Document

10.1109/CEC45853.2021.9504910

Cite this

@inproceedings{e525ca0ad021456e97cb5bd76c78650e,

title = "Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders",

keywords = "Autoencoder, Evolutionary design, Fitness landscape, Genetic representation, Latent representation",

author = "Piotr Kaszuba and Maciej Komosinski and Agnieszka Mensfelt",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE Congress on Evolutionary Computation, CEC 2021 ; Conference date: 28-06-2021 Through 01-07-2021",

year = "2021",

month = aug,

day = "9",

doi = "10.1109/CEC45853.2021.9504910",

language = "English",

pages = "1123--1130",

booktitle = "2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Kaszuba, P, Komosinski, M & Mensfelt, A 2021, Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders. in 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., pp. 1123-1130, 2021 IEEE Congress on Evolutionary Computation, CEC 2021, Virtual, Krakow, Poland, 28/06/21. https://doi.org/10.1109/CEC45853.2021.9504910

Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders. / Kaszuba, Piotr; Komosinski, Maciej; Mensfelt, Agnieszka.
2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1123-1130.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders

AU - Kaszuba, Piotr

AU - Komosinski, Maciej

AU - Mensfelt, Agnieszka

PY - 2021/8/9

Y1 - 2021/8/9

KW - Autoencoder

KW - Evolutionary design

KW - Fitness landscape

KW - Genetic representation

KW - Latent representation

UR - http://www.scopus.com/inward/record.url?scp=85124612234&partnerID=8YFLogxK

U2 - 10.1109/CEC45853.2021.9504910

DO - 10.1109/CEC45853.2021.9504910

M3 - Conference contribution

AN - SCOPUS:85124612234

SP - 1123

EP - 1130

BT - 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE Congress on Evolutionary Computation, CEC 2021

Y2 - 28 June 2021 through 1 July 2021

ER -

Automated Development of Latent Representations for Optimization of Sequences Using Autoencoders

Conference

Keywords

Access to Document

Other files and links

Cite this