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From "Edward J. Yoon" <edward.y...@samsung.com>
Subject RE: Implement convolutional neuron function
Date Tue, 19 Jan 2016 05:16:58 GMT
Hi,

As described in "Convolution Demo" section of 
http://cs231n.github.io/convolutional-networks, convolution layer construct 
output maps by convoluting trainable kernel filter. Animation will be very 
helpful. The initial weights of kernel filter are random like MLP. And, this 
convolution computation between a feature map and a kernel can be simplified 
to a vector/matrix multiplication. The batch of multiple images is mat-mat 
multiplication. This is normal way in other projects like Torch.

Instead we doing like that, we'll do element-wise multiplication within each 
neuron object. User define the neuron function then, framework process the 
neurons in parallel. To understand this flow, Pregel system will be helpful.

I roughly guess our system can be useful when if a server receive image to 
recognize. Because, GPU-oriented systems are optimized to process batch 
operations.

--
Best Regards, Edward J. Yoon


-----Original Message-----
From: Zachary Jaffee [mailto:zij@case.edu]
Sent: Tuesday, January 19, 2016 1:34 PM
To: Unknown
Subject: Re: Implement convolutional neuron function

So I've tried out a few things, but I can't seem to see what you mean when
you say not to use a dot product. If you have any insights as to what this
function would look like, I'd be interested in seeing what you are thinking
of.

On Wed, Dec 16, 2015 at 6:29 PM, Edward J. Yoon <edward.yoon@samsung.com>
wrote:

> Thanks.
>
> You can discuss this issue with me and shubham.
>
> I personally we need to approach neuron-centric instead of dot product of
> matrix or tensor, so that we can parallelize computations at neuron level.
> In
> here, the tricky issue is handling the topology of neurons within
> rectangular
> grid (graph structure). But, you can ignore this at the moment.
>
> If you have any questions/opinions, let's discuss together.
>
> --
> Best Regards, Edward J. Yoon
>
> -----Original Message-----
> From: Zachary Jaffee [mailto:zij@case.edu]
> Sent: Thursday, December 17, 2015 12:59 AM
> To: Unknown
> Subject: Re: Implement convolutional neuron function
>
> I'll take care of this.
>
> On Wed, Dec 16, 2015 at 2:26 AM, Edward J. Yoon <edward.yoon@samsung.com>
> wrote:
>
> > Hi forks,
> >
> > Does anyone volunteer for HORN-10?
> >
> > To implement convolutional neuron function, you can refer my standard
> > neuron
> > function code here:
> >
> >
> https://github.com/edwardyoon/incubator-horn/blob/HORN-7/src/test/java/org/a
> > pache/horn/trainer/TestNeuron.java
> >
> > And basic equation
> >
> >
> https://jianfengwang.files.wordpress.com/2015/07/forwardandbackwardpropagati
> > onofconvolutionallayer.pdf and animation version can be found at
> > http://cs231n.github.io/convolutional-networks/ for forward and backward
> > of
> > convolutional neuron.
> >
> > Thanks!
> >
> > --
> > Best Regards, Edward J. Yoon
> >
> >
> >
> >
>
>
> --
> Zach Jaffee
> B.S. Computer Science
> Case Western Reserve University Class of 2017
> Operations Director | WRUW FM 91.1 Cleveland
> Secretary | Recruitment Chair | Phi Kappa Theta Fraternity
> (917) 881-0646
> zjaffee.com
> github.com/ZJaffee
>
>
>


-- 
Zach Jaffee
B.S. Computer Science
Case Western Reserve University Class of 2017
Operations Director | WRUW FM 91.1 Cleveland
Secretary | Recruitment Chair | Phi Kappa Theta Fraternity
(917) 881-0646
zjaffee.com
github.com/ZJaffee



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