02417nam0 22004093i 450 CAG045996120170908093253.0849614244220090525d2003 ||||0itac50 baitaitz01i xxxe z01nFahrenheit 451Ray Bradburytraduzione di Giorgio MonicelliRomaLa biblioteca di Repubblicac2003190 p.22 cm˜La Âœbiblioteca di Repubblica. Novecento72Suppl. a: La Repubblica.001MIL05424002001 ˜La Âœbiblioteca di Repubblica. Novecento72Fahrenheit 451.CFI0023628CFIV007830278009Narrativa americanaFIRNAPC173069IBradbury, RayCFIV007830070457515Monicelli, GiorgioCFIV037675730Bradbury, Ray DouglasSBNV038811Bradbury, RayITIT-NA007920090525IT-NA0537IT-NA0299IT-NA0768IT-AV0126IT-AV0195IT-NA0580IT-NA0312CAG0459961Biblioteca Comunale di Villaricca 68LETTER. Biblioteca di RepubblicaL 1. n.72 68 0000028905 B 1 v.D 2004020120040201Biblioteca comunale di Afragola AGII S.10.19 AG 0000120585 B 2015111220151112Biblioteca Annalisa Durante1 v. DULETT. Prosa BRA fa DU 0000047885 B 1 v.T 2017051820170518Biblioteca civica "Can. Marciano De Leo"1 v. FRB 002. 132 FR 0000008895 B 1 v.T 2012072420120724Biblioteca Mario Pensa del Liceo statale Paolo Emilio Imbriani1 v. LIAR10 002. 098 LI 0000007615 B 1 v.T 2017032820170328Biblioteca del Pontificio Santuario Beata Vergine del Rosario1 v. PSSALA A C.17.2. 29 PS 0000019505 B 1 v.Z 2015120720151207Istituto Salesiano Sacro Cuore1 v.1 v. SC36 05 015 SC01 0000140865 B 1 v.T 2009052520090525 68 AG DU FR LI PS SCFahrenheit 451278009UNISANNIO06769nam 22006613u 450 99646455210331620230221132630.0981-16-4095-5(CKB)5340000000068377EBL6787726(OCoLC)1313880904(AU-PeEL)EBL6787726(MiAaPQ)EBC6787726(oapen)https://directory.doabooks.org/handle/20.500.12854/72797(PPN)258302194(EXLCZ)99534000000006837720220617d2021|||| u|| |engur|n|---|||||txtrdacontentcrdamediacrrdacarrierSublinear Computation Paradigm[electronic resource] Algorithmic Revolution in the Big Data EraSingapore Springer Singapore Pte. Limited20211 online resource (403 p.)Description based upon print version of record.981-16-4094-7 Intro -- Preface -- Contents -- Part I Introduction -- 1 What Is the Sublinear Computation Paradigm? -- 1.1 We Are in the Era of Big Data -- 1.2 Theory of Computational Complexity and Polynomial-Time Algorithms -- 1.3 Polynomial-Time Algorithms and Sublinear-Time Algorithms -- 1.3.1 A Brief History of Polynomial-Time Algorithms -- 1.3.2 Emergence of Sublinear-Time Algorithms -- 1.3.3 Property Testing and Parameter Testing -- 1.4 Ways to Decrease Computational Resources -- 1.4.1 Streaming Algorithms -- 1.4.2 Compression -- 1.4.3 Succinct Data Structures1.5 Need for the Sublinear Computation Paradigm -- 1.5.1 Sublinear and Polynomial Computation Are Both Important -- 1.5.2 Research Project ABD -- 1.5.3 The Organization of This Book -- References -- Part II Sublinear Algorithms -- 2 Property Testing on Graphs and Games -- 2.1 Introduction -- 2.2 Basic Terms and Definitions for Property Testing -- 2.2.1 Graphs and the Three Models for Property Testing -- 2.2.2 Properties, Distances, and Testers -- 2.3 Important Known Results in Property Testing on Graphs -- 2.3.1 Results for the Dense-Graph Model -- 2.3.2 Results for the Bounded-Degree Model2.3.3 Results for the General-Graph Model -- 2.4 Characterization of Testability on Bounded-Degree Digraphs -- 2.4.1 Bounded-Degree Model of Digraphs -- 2.4.2 Monotone Properties and Hereditary Properties -- 2.4.3 Characterizations -- 2.4.4 An Idea to Extend the Characterizations Beyond Monotone and Hereditary -- 2.5 Testable EXPTIME-Complete Games -- 2.5.1 Definitions -- 2.5.2 Testers for Generalized Chess, Shogi, and Xiangqi -- 2.6 Summary -- References -- 3 Constant-Time Algorithms for Continuous Optimization Problems -- 3.1 Introduction -- 3.2 Graph Limit Theory3.3 Quadratic Function Minimization -- 3.3.1 Proof of Theorem 3.1 -- 3.4 Tensor Decomposition -- 3.4.1 Preliminaries -- 3.4.2 Proof of Theorem 3.2 -- 3.4.3 Proof of Lemma 3.4 -- 3.4.4 Proof of Lemma 3.5 -- References -- 4 Oracle-Based Primal-Dual Algorithms for Packing and Covering Semidefinite Programs -- 4.1 Packing and Covering Semidefinite Programs -- 4.2 Applications -- 4.2.1 SDP relaxation for Robust MaxCut -- 4.2.2 Mahalanobis Distance Learning -- 4.2.3 Related Work -- 4.3 General Framework for Packing-Covering SDPs -- 4.4 Scalar Algorithms4.4.1 Scalar MWU Algorithm for (Packing-I)-(Covering-I) -- 4.4.2 Scalar Logarithmic Potential Algorithm For (Packing-I)-(Covering-I) -- 4.5 Matrix Algorithms -- 4.5.1 Matrix MWU Algorithm For (Covering-II)-(Packing-II) -- 4.5.2 Matrix Logarithmic Potential Algorithm For (Packing-I)-(Covering-I) -- 4.5.3 Matrix Logarithmic Potential Algorithm For (Packing-II)-(Covering-II) -- References -- 5 Almost Linear Time Algorithms for Some Problems on Dynamic Flow Networks -- 5.1 Introduction -- 5.2 Preliminaries -- 5.3 Objective Functions -- 5.3.1 Objective Functions for the 1-Sink Problem5.3.2 Objective Functions for k-SinkThis 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. The book consists of five parts: Part I, which consists of a single chapter on the concept of the sublinear computation paradigm; Parts II, III, and IV review results on sublinear algorithms, sublinear data structures, and sublinear modelling, respectively; Part V presents application results. The information presented here will inspire the researchers who work in the field of modern algorithms.Algorithms & data structuresbicsscNumerical analysisbicsscSublinear Algorithmspolynomial time algorithmsConstant-Time AlgorithmsSublinear Computation Paradigmopen accessAlgorithms & data structuresNumerical analysisKatoh Naoki1238685Higashikawa Yuya1238686Ito Hiro1238687Nagao Atsuki1238688Shibuya Tetsuo1238689Sljoka Adnan1238690Tanaka Kazuyuki1238691Uno Yushi1073569AU-PeELAU-PeELAU-PeELBOOK996464552103316Sublinear Computation Paradigm2874616UNISA00672nam a2200181 i 450099100431223770753620240315101900.0240315s1994 sp r 001 0 spa 8433913789Bibl. Dip.le Aggr. Scienze Giuridiche - Sez. Centro Studi sul RischioitaLipovetsky, Gilles143851El crepuscolo del deber :La etica indolora de los nuevos tiempos democraticos /Gilles Lipovetsky ; traduccion de Juana Bignozzi2. ed.Barcelona :Editorial Anagrama,1994Collecion Argumentos991004312237707536Crepuscolo del deber4132952UNISALENTO