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September 2013 On statistics, computation and scalability
Michael I. Jordan
Bernoulli 19(4): 1378-1390 (September 2013). DOI: 10.3150/12-BEJSP17

Abstract

How should statistical procedures be designed so as to be scalable computationally to the massive datasets that are increasingly the norm? When coupled with the requirement that an answer to an inferential question be delivered within a certain time budget, this question has significant repercussions for the field of statistics. With the goal of identifying “time-data tradeoffs,” we investigate some of the statistical consequences of computational perspectives on scability, in particular divide-and-conquer methodology and hierarchies of convex relaxations.

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Michael I. Jordan. "On statistics, computation and scalability." Bernoulli 19 (4) 1378 - 1390, September 2013. https://doi.org/10.3150/12-BEJSP17

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Published: September 2013
First available in Project Euclid: 27 August 2013

zbMATH: 1273.62030
MathSciNet: MR3102908
Digital Object Identifier: 10.3150/12-BEJSP17

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

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Vol.19 • No. 4 • September 2013
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