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2013

Fast Training of Convolutional Networks through FFTs

Mathieu, Michael, Henaff, Mikael, LeCun, Yann

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Understand

Convolutional networks are one of the most widely employed architectures in computer vision and machine learning.

In order to leverage their ability to learn complex functions, large amounts of data are required for training.
Training a large convolutional network to produce state-of-the-art results can take weeks, even when using modern GPUs.
Producing labels using a trained network can also be costly when dealing with web-scale datasets.

Fast Training of Convolutional Networks through FFTs · Around

Built on

An algorithm for the machine calculation of complex fourier series
James Cooley and John Tukey · 1965
Earlier work this paper cites.
Efficient backprop
Y. LeCun, L. Bottou, G. Orr, and K. Muller · 1998
Earlier work this paper cites.
Fast face detection using mlp and fft
S. Ben-Yacoub, B. Fasel, and J. Luttin · 1999
Earlier work this paper cites.
Musical genre classification of audio signals
G. Tzanetakis and P. Cook · 2002
Earlier work this paper cites.

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