Home > Uncategorized > Weekly QuEST Discussion Topics and News, 13 Nov

Weekly QuEST Discussion Topics and News, 13 Nov

QuEST 13 Nov 2015

This week we will first continue our discussion of big data and QuEST and Deep learning – we will review the information from the guest lecture by Prof Mixon

He gave the local QuEST guys a lecture: Recent advances in mathematical data science

This talk describes three different problems of interest in mathematical data science. First, we consider the problem of compressive classification, in which one seeks to classify data from compressed measurements. Next, we consider a semidefinite relaxation of the k-means problem to establish clustering guarantees under a certain data model. Finally, we recast the general problem of binary classification as a sparse approximation problem, and we observe numerical evidence of the efficacy of this approach

Next we will discuss the couple of slides we need to add on the topic of Big Data to our ‘Kabrisky lecture’ – “What is QuEST?’ deck on the topic – we give the Kabrisky Lecture the first meeting of the calendar year – it will 8 Jan 2016 at noon eastern.

After that discussion on what slides to add that summarize QuEST and big Data / deep learning – I want to spend a couple of minutes talking about an effort that came out of the naval post graduate school (NPS) – “Global Information Network Archtecture = GINA” – our colleagues that work in this area spent some time while I was out last week adapting their efforts to our QuEST terminology – I will briefly attempt to familiarize the group with the effort and post some GINA material on the internal QuEST site for those interested in pursuing it.

Next we want to continue our review of the material we’ve covered this calendar year for possible inclusion into the Kabrisky Lecture slide deck – one such topic is ‘meaning’ – so we will spend some time discussing what we’ve concluded about ‘meaning’ and what couple of slides capture the key ideas for inclusion.

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