Well, have fun and give her our regards. You missed a good S.A.R. lecture tonight, but a not so good dinner at that hotel across the street from the back side of the history museum that is not the Inn of the Anisaze.
Travel safe, T*D On Thu, Oct 24, 2013 at 8:35 PM, George Duncan <[email protected]> wrote: > Ah, big data and big computing! > > Interesting that this relates to what I did for my masters paper in > statistics at the University of Chicago. But I was no where near so > sophisticated and of course had no big computing back in 1964! > > Off to Aunt Mabel's 100 tomorrow am! > > George Duncan > georgeduncanart.com > (505) 983-6895 > Represented by ViVO Contemporary > 725 Canyon Road > Santa Fe, NM 87501 > > Dynamic application of matrix order and luminous chaos. > > > On Thu, Oct 24, 2013 at 5:19 PM, Tom Johnson <[email protected]> wrote: > >> >> http://www.datasciencecentral.com/profiles/blogs/ibm-distinguished-engineer-solves-big-data-conjecture >> BM Distinguished Engineer solves Big Data Conjecture >> >> - Posted by Vincent >> Granville<http://www.datasciencecentral.com/profile/VincentGranville>on >> October 23, 2013 at 3:28pm >> - View >> Blog<http://www.datasciencecentral.com/profiles/blog/list?user=3v6n5b6g08kgn> >> >> A mathematical problem related to big data was solved by Jean-Francois >> Puget, engineer in the Solutions Analytics and Optimization group at IBM >> France. The problem was first mentioned on Data Science Central, and an >> award was offered to the first data scientist to solve it. >> >> Bryan Gorman, Principal Physicist, Chief Scientist at Johns Hopkins >> University Applied Physics Laboratory, made a significant breakthrough in >> July, and won $500. Jean-Francois Puget completely solved the problem, >> independently from Bryan, and won a $1,000 award. >> >> *Example of rare, special permutation investigated to prove the theorem* >> >> The competition has been organized and financed by Data Science central. >> Participants from around the world submitted a number of interesting >> approaches. The mathematical question was asked by Vincent Granville, a >> leading data scientist and co-founder at Data Science Central. Granville >> initially proposed a solution after performing large-scale Monte Carlo >> simulations, but his solution turned out to be wrong. >> >> The problem consisted in finding an exact formula for a new type of >> correlation and goodness-of-fit metrics, designed specifically for big >> data, generalizing the Spearman's rank coefficient, and being especially >> robust for non-bounded, ordinal data found in large data sets. From a >> mathematical point of view, the new metric is based on L-1 rather than L-2 >> theory: In other words, it relies on absolute rather than squared >> differences. Using squares (or higher powers) is what makes traditional >> metrics such as R squared notoriously sensitive to outliers, and avoided by >> savvy statistical modelers. In big data, outliers are plentiful and it can >> render conclusions from a statistical analysis invalid, so this is a >> critical issue. This outlier issue is sometimes referred to as *the >> curse of big >> data*.....[more<http://www.datasciencecentral.com/profiles/blogs/ibm-distinguished-engineer-solves-big-data-conjecture> >> ] >> >> >> -tj >> >> >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com > -- ========================================== J. T. Johnson Institute for Analytic Journalism -- Santa Fe, NM USA<http://www.analyticjournalism.com/> 505.577.6482(c) 505.473.9646(h) Twitter: jtjohnson slideshare.net/jtjohnson/presentations http://www.jtjohnson.com [email protected] ==========================================
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