Re: [Nmlrg] Call for Agenda NMLRG @IETF94, Yokohama

Hi Jerome,

I feel the topic interesting and should be valuable for discussion. 
Please find some specific comments inline.

> -----Original Message-----
> From: nmlrg [mailto:nmlrg-bounces@irtf.org] On Behalf Of Jér?me Fran?ois
> Sent: Tuesday, October 13, 2015 4:21 AM
> To: nmlrg@irtf.org
> Subject: Re: [Nmlrg] Call for Agenda NMLRG @IETF94, Yokohama
> 
> Hi all,
> 
> I recently introduced a fingerprinting use case on the ML that I could present
> but I was wondering if it would not better to present something about
> heterogenous data aggregation.
> 
> We actually build a method to aggregate multi-dimensional data within a
> single tree structure without assuming any order between dimensions and
> with variable granularity. 
[Bing] I guess most of the raw data is more or less mix-dimensional. Orthogonal data should be a fine-tuned result most of the time.
So, I guess your aggregation method should be common in some degree, that not only applied to your fingerprinting use case?

> It is a kind of mix between k-dimensional tree and density-based clustering. 
> For example, we applied it to DNS answers
> aggregating both domain names and IP address in a single data structure to
> be analyzed rather than an individual record inspection to first identify time
> period where some divergent behavior appears.
[Bing] This sounds interesting. An naive question: can this algorithm be applied to network traffic N-tuples analysis, and is there any limitation to the number of "N"?

> I know that it is not ML itself but we used it is fully in the scope of data
> representation and pre-processing of ML.
[Bing] Pre-processing might not be the key factor in ML theory/methodology perspective; but it is curtail in ML engineering perspective. So I'd like to hear it in your presentation.

Best regards,
Bing

> So, would that topic be interesting for NMLRG participants?
> 
> Best regards,
> jerome
> 
> Le 08/10/2015 05:28, Sheng Jiang a écrit :
> > Hi, all,
> >
> > We have been assigned one session of 2.5 hour for the proposed NMLRG
> > (Network Machine Learning Research Group) meeting for
> > IETF-94 (Yokohama) and are starting to collect agenda items for this
> > session.
> >
> > The proposed NML RG is still in the very initial stage. So, we have
> > very open scope. We do not restrict the topics. The only threshold is
> > it should be relevant to network or network devices, using Machine
> Learning.
> >
> > Please send us (jiangsheng@huawei.com, brian.e.carpenter@gmail.com)
> > requests for sessions and include:
> >
> > Name of time slot:
> > Name of topic(s):
> > Time requested:
> > Presenter name(s):
> > Brief description of the topic:
> >
> > More details about the Yokohama IETF can be found at
> > http://www.ietf.org/meeting/94/index.html.
> >
> > Also, presenters please invoke discussions in the NMLRG list. We have
> > limited time in the face-to-face meeting. Mail list is a good place to
> > propagate and discuss the topics.
> >
> > Best regards,
> >
> > Brian & Sheng
> > _______________________________________________
> > nmlrg mailing list
> > nmlrg@irtf.org
> > https://www.irtf.org/mailman/listinfo/nmlrg
> 
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