I'm planning to have a talk that probably lasts closer to 30 minutes than 60 minutes, so we'll have plenty of time after to get the historical narrative correct.

I will also try to give people some intuition to explain how the FFT manages to "cheat" at computing, but I'm not going to try to cram a full course on signal processing into a tea talk.


On Tue, May 27, 2014 at 1:49 PM, Liu, Xiaohua <Xiaohua.Liu@nuance.com> wrote:

FYI.  This paper titled “A Convolutional Neural Network for Modelling Sentences”  also mentioned FFT for convolution computation.

 

Thanks,

Xiaohua

 

From: lisa_teatalk-bounces@iro.umontreal.ca [mailto:lisa_teatalk-bounces@iro.umontreal.ca] On Behalf Of Ian Goodfellow
Sent: Tuesday, May 27, 2014 1:46 PM
To: Kyung Hyun Cho
Cc: Lisa Labo; lisa_teatalk@iro.umontreal.ca
Subject: Re: [Lisa_teatalk] [Lisa_labo] Tea Talk Tomorrow 28 May @13:00 AA3195 by Guillaume Alain

 

FFTs have been used to speed up convolution since at least the 1960s. I'm not sure why this isn't done more in the neural nets community, but this year's ICLR paper is not the place where the idea was first proposed.

 

2014-05-27 13:21 GMT-04:00 Kyung Hyun Cho <cho.k.hyun@gmail.com>:

Dear all,

Guillaume Alain will tell us about the recently proposed technique of using FFT for fast convolutional operation tomorrow. See below for the detail.

See you there!

- Cho

============

- Speaker: Guillaume Alain

- Date and Time: 28 May 2014 @ 13.00

- Place: AA3195

- Paper to be Discussed: Michael Mathieu, Mikael Henaff, Yann LeCun. Fast Training of Convolutional Networks through FFTs. ICLR 2014


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