Self-supervised autoencoders for clustering and classification

Clustering techniques aim at finding meaningful groups of data samples which exhibit similarity with regards to a set of characteristics, typically measured in terms of pairwise distances. Due to the so-called curse of dimensionality, i.e., the observation that high-dimensional spaces are unsuited f...

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Vydané v:	Evolving systems Ročník 11; číslo 3; s. 453 - 466
Hlavní autori:	Nousi, Paraskevi, Tefas, Anastasios
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020
Predmet:	Artificial Intelligence Complex Systems Complexity Engineering Original Paper Dimensionality reduction Deep learning Clustering Autoencoders Classification
ISSN:	1868-6478, 1868-6486
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