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by Nina Zumel
Principal Consultant Win-Vector LLC

We've just finished off a series of articles on some recent research results applying differential privacy to improve machine learning. Some of these results are pretty technical, so we thought it was worth working through concrete examples. And some of the original results are locked behind academic journal paywalls, so we've tried to touch on the highlights of the papers, and to play around with variations of our own.

The R Consortium Infrastructure Steering Committee (chaired by Hadley Wickham) announced today the award of its first grant for an R community development project: $85,000 to Gábor Csárdi to implement the

I really like this visualization (via FlowingData) of the most common motions of chess pieces, according to the 2million+ games in the fdsf dataset. Here's the chart for the black knight, which does a good job of scouting the entire board:

and here's the black bishop:

At the PASS Summit in Seattle this week, Microsoft's Jason Wilcox and Gopi Kumar demonstrated a SQL Server 2016 application that embeds R to predict what time you need to leave to catch a flight, given traffic, check-in time, and the likelihood of a flight leaving early or being delayed.


by Joseph Rickert

We all "know" that correlation does not imply causation, that unmeasured and unknown factors can confound a seemingly obvious inference. But, who has not been tempted by the seductive quality of strong correlations?

by Hong Ooi
Sr. Data Scientist, Microsoft

by Andrie de Vries

Recently we had a question on the public mailing list for Revolution R Open (RRO), on the topic of "MKL multithreaded library and mclapply do not play well together".

If you're not familiar with these topics, here is a quick primer: