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

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse
Department of Mechanical and Industrial Engineering and the Iowa Informatics Initiative, The University of Iowa, Iowa City, IA 52242-1527, USA
IEEE Access, Volume: PP, Issue: 99, 2015

@article{akusok2015high,

   title={High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications},

   author={Akusok, Anton and Bjork, Kaj-Mikael and Miche, Yoan and Lendasse, Amaury},

   publisher={IEEE},

   year={2015}

}

This work 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 Extreme Learning Machines to the widest range of users.
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