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Authors: Panagiotis C. Petrantonakis and Ioannis Kompatsiaris

Affiliation: Information Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece

Keyword(s): Particle Swarm Optimization, Data Visualization, Dimensionality Reduction.

Abstract: Dimensionality reduction involves mapping of a set of high dimensional input points on a low dimensional space. Mappings in low dimensional space are expected to preserve the pairwise distances of the high dimensional inputs. In this work we present a dimensionality reduction method, called Dimensionality Reduction based on Particle Swarm Optimization (PSO-DR), where the conversion of each input to the low dimensional output does not depend on the rest of the inputs but, instead, it is based on a set of reference points (beacons). The presented approach results in a simple, fast, versatile dimensionality reduction approach with good quality of visualization and straightforward out-of-sample extension.

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Paper citation in several formats:
Petrantonakis, P. and Kompatsiaris, I. (2020). A Dimensionality Reduction Method for Data Visualization using Particle Swarm Optimization. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - ECTA; ISBN 978-989-758-475-6; ISSN 2184-3236, SciTePress, pages 131-138. DOI: 10.5220/0010020601310138

@conference{ecta20,
author={Panagiotis C. Petrantonakis. and Ioannis Kompatsiaris.},
title={A Dimensionality Reduction Method for Data Visualization using Particle Swarm Optimization},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - ECTA},
year={2020},
pages={131-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010020601310138},
isbn={978-989-758-475-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - ECTA
TI - A Dimensionality Reduction Method for Data Visualization using Particle Swarm Optimization
SN - 978-989-758-475-6
IS - 2184-3236
AU - Petrantonakis, P.
AU - Kompatsiaris, I.
PY - 2020
SP - 131
EP - 138
DO - 10.5220/0010020601310138
PB - SciTePress

- Science and Technology Publications, Lda.
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