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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.
| Originalspråk | Odefinierat/okänt |
|---|---|
| Referentgranskad vetenskaplig tidskrift | IEEE Access |
| Volym | 3 |
| Sidor (från-till) | 1011-1025 |
| Antal sidor | 15 |
| DOI | |
| Status | Publicerad - 2015 |
| MoE-publikationstyp | A1 Originalartikel i en vetenskaplig tidskrift |
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