Hi all,

My supervisor updated his page. You can get our papers here:
http://www.ict.griffith.edu.au/~johnt/publications.html.

There is the most recent paper on sparse codes plus some of our other
papers.


On 16 March 2014 02:07, Traun Leyden <[email protected]> wrote:

> Hi Adam,
>
> Yes I'd be interested in getting a copy.  I'd prefer a README and a github
> repo, but I'll take what I can get!
>
>
>
> On Thu, Mar 13, 2014 at 3:35 PM, Adam Kneller <
> [email protected]> wrote:
>
>> Hi,
>>
>> My supervisor is the lead author on that paper. It uses the old version
>> of the HTM, not the CLA. We have some more recent papers dealing with digit
>> recognition that use the CLA, e.g. Evaluating Sparse Codes on Handwritten
>> Digits (http://link.springer.com/chapter/10.1007/978-3-319-03680-9_40).
>>
>> Let me know if you don't have Springer access and I will hopefully be
>> able to get yo a copy.
>>
>> Adam.
>>
>>
>> On 13 March 2014 01:36, Traun Leyden <[email protected]> wrote:
>>
>>>
>>> Yep, fair enough.  It sounds like you would need more than just a
>>> spatial pooler here.
>>>
>>> I've found this paper which seems to be trying to tackle the same
>>> problem: http://www.ict.griffith.edu.au/~johnt/publications/AI2008.pdf
>>>
>>> but unfortunately don't know where the accompanying source code is (or
>>> if it's available).
>>>
>>> Btw if you think this repo would be good to put in the examples
>>> directory, I'd be happy to send a PR.
>>>
>>>
>>> On Mon, Mar 10, 2014 at 8:33 AM, Matthew Taylor <[email protected]>wrote:
>>>
>>>> To quote Subutai from another thread [1]:
>>>>
>>>> "You might not get an exact match unless the inputs are really really
>>>> close. In particular, the spatial pooler won't do too well at learning
>>>> general invariances (and it's not supposed to). For example, if you
>>>> shift the image by one or two pixels you might get a very different
>>>> output SDR."
>>>>
>>>> [1] http://markmail.org/message/dytllixwodm5bjcu
>>>> ---------
>>>> Matt Taylor
>>>> OS Community Flag-Bearer
>>>> Numenta
>>>>
>>>>
>>>> On Sun, Mar 9, 2014 at 12:27 PM, Traun Leyden <[email protected]>
>>>> wrote:
>>>> >
>>>> > I created a simple example to recognize digits using the spatial
>>>> pooler,
>>>> > it's available on github here:
>>>> >
>>>> > https://github.com/tleyden/nupic-digitrecognizer
>>>> >
>>>> > It was able to get exact matches with SDR's, and I didn't need to use
>>>> the
>>>> > KNNClassifier.  Having said that, the test data was relatively
>>>> "easy", in
>>>> > that I just went through the training data and removed a few pixels.
>>>> >
>>>> > However when I tried to recognize a digit that's been entirely
>>>> shifted to
>>>> > the right by a few pixels (original - shifted) it wasn't able to find
>>>> a
>>>> > match.
>>>> >
>>>> > What are some suggested approaches to add spatial invariance so it can
>>>> > handle this?
>>>> >
>>>> > I did see this mailing list thread but so far no simple answer has
>>>> jumped
>>>> > out at me.
>>>> >
>>>> > Also thanks to all the folks who responded to my questions, those were
>>>> > useful pointers.
>>>> >
>>>> >
>>>> >
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>>>> >
>>>>
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