Towards enhancing stacked extreme learning machine with sparse autoencoder by correntropy

@article{Luo2017TowardsES,
  title={Towards enhancing stacked extreme learning machine with sparse autoencoder by correntropy},
  author={Xiong Luo and Yong Xu and Weiping Wang and Manman Yuan and Xiaojuan Ban and Yueqin Zhu and Wenbing Zhao},
  journal={J. Frankl. Inst.},
  year={2017},
  volume={355},
  pages={1945-1966}
}
  • Xiong Luo, Yong Xu, +4 authors Wenbing Zhao
  • Published in J. Frankl. Inst. 2017
  • Computer Science, Mathematics
  • Abstract The stacked extreme learning machine (S-ELM) is an advanced framework of deep learning. It passes the ‘reduced’ outputs of the previous layer to the current layer, instead of directly propagating the previous outputs to the next layer in traditional deep learning. The S-ELM could address some large and complex data problems with a high accuracy and a relatively low requirement for memory. However, there is still room for improvement of the time complexity as well as robustness while… CONTINUE READING

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