Algorithms Column: Sublinear time algorithms Ravi Kumar Ronitt Rubinfeld Column editor s note This issue s column is written by guest columnists, Ravi Kumar and Ronitt Rubinfeld. I am delighted that they agreed to write the column at such short notice. Sublinear time algorithms have received a lot of attention recently, and their timely column introduces the reader to several recent results and provides references for further readings. Samir Khuller Introduction With the recent tremendous increase in computational power and cheap storage, we are blessed with a multitude of available, and possibly useful, information. It is always nice to have something for (almost) nothing. However, this blessing is also something of a curse, for we may also be asked to do something meaningful with all of this data. The scale of these data sets, coupled with the typical situation in which there is very little time to perform our computations, raises the question of which computations could one hope to accomplish extremely quickly? In particular, what can one solve in sublinear time? Sublinear time is a daunting goal since it allows one to read only a miniscule fraction of the input. Still, there are problems for which
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Algorithms column: sublinear time algorithms
Kumar, Ravi; Rubinfeld, Ronitt
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, Volume 34 (4)
Association for Computing Machinery – Dec 1, 2003
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