Re: [Nmlrg] One comment on the proposed charter...

David Meyer <dmm@1-4-5.net> Thu, 30 June 2016 17:57 UTC

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From: David Meyer <dmm@1-4-5.net>
Date: Thu, 30 Jun 2016 10:57:13 -0700
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To: Sheng Jiang <jiangsheng@huawei.com>
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Cc: "nmlrg@irtf.org" <nmlrg@irtf.org>, Ed Henry <networkn3rd@gmail.com>
Subject: Re: [Nmlrg] One comment on the proposed charter...
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On Thu, Jun 30, 2016 at 10:34 AM, Sheng Jiang <jiangsheng@huawei.com> wrote:

> Thanks David and Ed,
>
>
>
> This is indeed a good suggestion. I also like the openness although our
> traditional players in the network area, like operators and vendors, may
> not be as open as ML communities. So, I may soften requirements a
> little bit.  We could certainly add such text when the next time we modify
> the charter. There may be a chance to do so sometime later this year when
> we formally approved as a long-running IRTF research group, if we could get
> approval.
>
>
>

Thanks Sheng.

I'll just mention here that (a). the Internet has a long tradition of
openness, perhaps best exemplified by the IETF itself; I don't see a
compelling reason why "ML for networking" should be any different [0]. In
particular, all the same problems the exist here as existed in the early
days of networking, when close to everything was proprietary. In any event
if there is a compelling reason why we should admit closed/proprietary
solutions/proposals that should be called out explicitly (obviously I would
disagree with this as a charter item but it should be made explicit if that
is what people are thinking), and  (b). the ML environment is rapidly
changing and making progress requires collaboration and sharing of
knowledge; that usually doesn't happen around closed, proprietary solutions
(almost by definition).

Finally, since AFAIK the RG hasn't been formally chartered there will be a
charter review and revision cycle before formal chartering (at least that
has traditionally been the case).

Thx,

--dmm

[0] And again, as I mentioned in an earlier email, much of the progress we
see in the ML space derives directly or indirectly from the Open Science
tradition we see in the ML community.

Regards,
>
>
>
> Sheng
>
>
> ------------------------------
> *From:* nmlrg [nmlrg-bounces@irtf.org] on behalf of Ed Henry [
> networkn3rd@gmail.com]
> *Sent:* 30 June 2016 4:11
> *To:* David Meyer
> *Cc:* nmlrg@irtf.org
> *Subject:* Re: [Nmlrg] One comment on the proposed charter...
>
>
>
> On Wed, Jun 29, 2016 at 1:59 PM, David Meyer <dmm@1-4-5.net> wrote:
>
>>
>> All,
>>
>> I was just reviewing the proposed charter and one thing we might consider
>> adding is the open database item (formally standardized datasets). We need
>> this not only to make progress and to prove out how various approaches work
>> (or don't work), whether new approaches improve on existing methods, and
>> the like.
>>
>> More generally, the machine learning community has a long standing
>> tradition of open source, open data, and even open models (AlexNet,
>> GoogLeNet, etc are excellent examples of the later). The NMLRG should
>> strive to carry on these traditions, and they should probably be reflected
>> in the charter. Perhaps something like:
>>
>
> +1 On keeping this long standing tradition.
>
>
>> To "The Network Machine Learning Research Group (NMLRG) provides a forum
>> for researchers to explore the potential of machine learning technologies
>> for networks. In particular, the NMLRG will work on potential approaches
>> that apply machine learning technologies in network control, network
>> management, and supplying network data for upper-layer applications.'
>>
>> add something like
>>
>>
>> "In addition and to the extent possible, approaches proposed in the NMLRG
>> should be documented not only with traditional written documentation but
>> also with an open source reference implementation and open access to the
>> data used to verify the approach."
>>
>
>> or similar, again with the goal of supporting/carrying on the open
>> science approach that has been so successful to date in the ML community.
>>
>
> +1 again. Would it be possible to use a hosted service such as Github or
> the like for hosting code, documentation, and data-set(s)? I think,
> traditionally, there was some adversity to using a hosted service like
> Github, at least within the IETF, but in general the ML community rallies
> around this platform. So it would almost make sense in that respect.
>
>
>>
>> Thanks,
>>
>> --dmm
>>
>>
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>>
>