[Lisa_teatalk] [Lisa_labo] Tea Talk Tomorrow 28 May @13:00 AA3195 by Guillaume Alain

Guillaume Alain guillaume.alain.umontreal at gmail.com
Tue May 27 14:16:43 EDT 2014


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 at nuance.com>wrote:

>  FYI.  This paper titled “A Convolutional Neural Network for Modelling
> Sentences<https://www.google.ca/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCcQFjAA&url=http%3A%2F%2Fnal.co%2Fpapers%2FKalchbrenner_DCNN_ACL14&ei=A9CEU923HZWiyASU8YHQCw&usg=AFQjCNG3QPFybr_uJS-EHCLWxb2IncmyMQ&bvm=bv.67720277,d.b2U>”
>  also mentioned FFT for convolution computation.
>
>
>
> Thanks,
>
> Xiaohua
>
>
>
> *From:* lisa_teatalk-bounces at iro.umontreal.ca [mailto:
> lisa_teatalk-bounces at 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 at 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 at 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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