An Improved Deep Computation Model Based on Canonical Polyadic Decomposition

@article{Zhang2018AnID,
  title={An Improved Deep Computation Model Based on Canonical Polyadic Decomposition},
  author={Qingchen Zhang and Laurence Tianruo Yang and Zhikui Chen and Peng Kai Li},
  journal={IEEE Transactions on Systems, Man, and Cybernetics: Systems},
  year={2018},
  volume={48},
  pages={1657-1666}
}
Deep computation models achieve super performance for big data feature learning. However, training a deep computation model poses a significant challenge since a deep computation model typically involves a large number of parameters. Specially, it needs a high-performance computing server with a large-scale memory and a powerful computing unit to train a deep computation model, making it difficult to increase the size of a deep computation model further for big data feature learning on low-end… CONTINUE READING
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