Call for papers for Statistical Analysis and Data Mining

News

  • Author: Statistics Views
  • Date: 04 March 2014

Statistical Analysis and Data Mining has sent out a call for papers for a special issue on Distributed Computation for Statistical Methods at Scale.

Computing that can be distributed over many processors, within a machine or across a network, has never been so easy and available. The greatest impact of this can be seen in the building of very large systems to handle, manipulate and analyse data at scale.

These systems are usually built to exploit the MapReduce paradigm, that permits easy scaling of algorithms and is robust to
individual processor failure.

As interest moves to deeper analyses of data at large scale, the statistics community has an opportunity to make an impact in this area.

thumbnail image: Call for papers for Statistical Analysis and Data Mining

The Editors for this special issue are Simon Wilson (Trinity College Dublin), Deepak Agarwal (LinkedIn), Steve Scott (Google) and Marc Suchard (UCLA), who are seeking contributions that explore the development, implementation and
evaluation of statistical methods in distributed computing environments.

These methods include but are not restricted to:
• exploratory data analysis and visualisation
• statistical inference and prediction
• statistical computation

Both theoretical and applied work are welcomed. Methods that are implemented on a multi-core processor, graphical processing unit or on a system distributed over a network are all relevant.

To submit your paper, please visit mc.manuscriptcentral.com/sam. The final deadline for submission is June 2014.

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