| 書目名稱 | Sublinear Computation Paradigm | | 副標題 | Algorithmic Revoluti | | 編輯 | Naoki Katoh,Yuya Higashikawa,Yushi Uno | | 視頻video | http://file.papertrans.cn/882/881325/881325.mp4 | | 概述 | Provides the concept of sublinear computation paradigm.Discusses the innovative algorithms, data structures, and modeling techniques for big data.This is an Open Access book.Includes applications to r | | 圖書封面 |  | | 描述 | 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 techn | | 出版日期 | Book‘‘‘‘‘‘‘‘ 2022 | | 關鍵詞 | Sublinear Algorithms; polynomial time algorithms; Constant-Time Algorithms; Sublinear Computation Parad | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-16-4095-7 | | isbn_softcover | 978-981-16-4097-1 | | isbn_ebook | 978-981-16-4095-7 | | copyright | The Editor(s) (if applicable) and The Author(s) 2022 |
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