Growing Neural Gas – A Parallel Approach - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2013

Growing Neural Gas – A Parallel Approach

Lukáš Vojáček
  • Function : Author
  • PersonId : 994859
Jiří Dvorský
  • Function : Author
  • PersonId : 994861

Abstract

The paper deals with the high dimensional data clustering problem. One possible way to cluster this kind of data is based on Artificial Neural Networks (ANN) such as SOM or Growing Neural Gas (GNG). The learning phase of the ANN, which is time-consuming especially for large high-dimensional datasets, is the main drawback of this approach to data clustering. The parallel modification, Growing Neural Gas, and its implementation on the HPC cluster is presented in the paper. Some experimental results are also presented.
Fichier principal
Vignette du fichier
978-3-642-40925-7_38_Chapter.pdf (834.05 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01496086 , version 1 (27-03-2017)

Licence

Attribution

Identifiers

Cite

Lukáš Vojáček, Jiří Dvorský. Growing Neural Gas – A Parallel Approach. 12th International Conference on Information Systems and Industrial Management (CISIM), Sep 2013, Krakow, Poland. pp.408-419, ⟨10.1007/978-3-642-40925-7_38⟩. ⟨hal-01496086⟩
153 View
713 Download

Altmetric

Share

Gmail Facebook X LinkedIn More