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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Sublinear Computation Paradigm: Algorithmic Revolution in the Big Data Era

Sublinear Computation Paradigm: Algorithmic Revolution in the Big Data Era

Katoh, Naoki
Higashikawa, Yuya
Ito, Hiro

Paperback

General ComputersProgramming

ISBN10: 9811640971
ISBN13: 9789811640971
Publisher: Springer
Published: Oct 20 2021
Pages: 410
Weight: 1.29
Height: 0.86 Width: 6.14 Depth: 9.21
Language: English
This open access book gives an overview of cutting-edge work on a new paradigm called the sublinear computation paradigm, which was proposed in the large multiyear academic research project Foundations of Innovative Algorithms for Big Data. That project ran from October 2014 to March 2020, in Japan. To handle the unprecedented explosion of big data sets in research, industry, and other areas of society, there is an urgent need to develop novel methods and approaches for big data analysis. To meet this need, innovative changes in algorithm theory for big data are being pursued. For example, polynomial-time algorithms have thus far been regarded as fast, but if a quadratic-time algorithm is applied to a petabyte-scale or larger big data set, problems are encountered in terms of computational resources or running time. To deal with this critical computational and algorithmic bottleneck, linear, sublinear, and constant time algorithms are required.

The sublinear computation paradigm is proposed here in order to support innovation in the big data era. A foundation of innovative algorithms has been created by developing computational procedures, data structures, and modelling techniques for big data. The project is organized into three teams that focus on sublinear algorithms, sublinear data structures, and sublinear modelling. The work has provided high-level academic research results of strong computational and algorithmic interest, which are presented in this book.

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