Very Efficient Training of Convolutional Neural Networks using Fast Fourier Transform and Overlap-and-Add

@inproceedings{Highlander2015VeryET,
  title={Very Efficient Training of Convolutional Neural Networks using Fast Fourier Transform and Overlap-and-Add},
  author={Tyler Highlander and Andres Rodriguez},
  booktitle={BMVC},
  year={2015}
}
Convolutional neural networks (CNNs) are currently state-of-the-art for various classification tasks, but are computationally expensive. Propagating through the convolutional layers is very slow, as each kernel in each layer must sequentially calculate many dot products for a single forward and backward propagation which equates to O(N2n2) per kernel per layer where the inputs are N×N arrays and the kernels are n× n arrays. Convolution can be efficiently performed as a Hadamard product in the… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 13 references

Going deeper with convolutions

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2015
View 1 Excerpt

Cufft library

CUDA Nvidia
http://docs.nvidia.com/cuda/cufft • 2010
View 2 Excerpts

Mnist handwritten digit database

Yann LeCun, Corinna Cortes
AT&T Labs [Online]. http://yann. lecun. com/exdb/mnist, • 2010
View 2 Excerpts

ImageNet: A large-scale hierarchical image database

2009 IEEE Conference on Computer Vision and Pattern Recognition • 2009
View 2 Excerpts

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