Sublinear Computation Paradigm Algorithmic Revolution in the Big Data Era

dc.contributor.authorNaoki Katoh
dc.contributor.authorYuya Higashikawa
dc.contributor.authorHiro Ito
dc.contributor.authorAtsuki Nagao
dc.date.accessioned2026-03-05T21:02:56Z
dc.date.available2026-03-05T21:02:56Z
dc.date.issued2022
dc.descriptionLibro electrónico
dc.description.abstractThis 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.
dc.identifier.isbn978-3-319-69623-964
dc.identifier.otherhttps://doi.org/10.1007/978-981-16-4095-7
dc.identifier.urihttps://link.springer.com/openurl?genre=book&isbn=978-981-16-4095-7
dc.identifier.urihttp://bibliovirtual.umar.mx:4000/handle/123456789/1915
dc.language.isoen_US
dc.publisherSpringer Nature Singapore
dc.titleSublinear Computation Paradigm Algorithmic Revolution in the Big Data Era
dc.typeBook
eperson.firstnamenombre
person.jobTitletrabajo

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