High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Amaury Lendasse

Forskningsoutput: TidskriftsbidragArtikelVetenskapligPeer review

220 Citeringar (Scopus)


This paper presents a complete approach to a successful utilization of a high-performance extreme learning machines (ELMs) Toolbox for Big Data. It summarizes recent advantages in algorithmic performance; gives a fresh view on the ELM solution in relation to the traditional linear algebraic performance; and reaps the latest software and hardware performance achievements. The results are applicable to a wide range of machine learning problems and thus provide a solid ground for tackling numerous Big Data challenges. The included toolbox is targeted at enabling the full potential of ELMs to the widest range of users.
Referentgranskad vetenskaplig tidskriftIEEE Access
Sidor (från-till)1011-1025
Antal sidor15
StatusPublicerad - 2015
MoE-publikationstypA1 Originalartikel i en vetenskaplig tidskrift


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