02636nam 2200469 450 991079717790332120200127090956.02-8062-6155-4(CKB)3710000000401428(EBL)2027817(MiAaPQ)EBC2027817(Au-PeEL)EBL2027817(OCoLC)908073805(PPN)233411461(EXLCZ)99371000000040142820200127d2015 uy 0freur|n|---|||||txtrdacontentcrdamediacrrdacarrierGeorges de La Tour, un peintre enigmatique De l'ombre a la lumiere /Tatiana Sgalbiero ; avec la collaboration d' Elisabeth Bruyns[Place of publication not identified] :50 Minutes,2015.1 online resource (35 p.)Artistes ;Numero 34Description based upon print version of record.2-8062-6156-2 Page de titre; Georges de la Tour; Contexte; L'Europe dans la tourmente; La situation de la France; L'art baroque; Biographie; Des débuts énigmatiques; Peintre du roi; De retour en Lorraine; Caractéristiques; Œuvres diurnes et œuvres nocturnes; Des sujets limités et un style très sobre; L'influence du Caravage; Sélection d'œuvres; Le Tricheur à l'as de carreau; Rixe de musiciens; Le Vielleur au chapeau; Le Nouveau-né; Georges de la Tour, une source d'inspiration; En résumé; Pour aller plus loin; Sources bibliographiques; Sources iconographiques; Sources complémentaires; Copyright Décryptez l'art de Georges de La Tour en moins d'une heure !Célébré de son vivant pour son art empruntant tant au Caravage qu'à ses suiveurs, Georges de La Tour sombre ensuite dans l'oubli le plus total. Ce n'est qu'au XIXe siècle qu'il est redécouvert, mais sa vie et son œuvre sont, aujourd'hui encore, entourées de mystère. Nimbées d'ombre et de silence, ses toiles tout en nuances lui valent aussitôt une place de choix dans l'histoire de l'art.Ce livre vous permettra d'en savoir plus sur : - Le contexte politique et culturel dans lequel évolue Georges de La Tour- La vie de l'artiste et son Artistes ;Numero 34.ArtHistoryArtHistory.709Sgalbiero Tatiana1477629Bruyns ElisabethMiAaPQMiAaPQMiAaPQBOOK9910797177903321Georges de La Tour, un peintre enigmatique3692884UNINA05372nam 22007215 450 991050428520332120251113190253.0981-16-4095-510.1007/978-981-16-4095-7(CKB)5340000000068377EBL6787726(OCoLC)1313880904(AU-PeEL)EBL6787726(MiAaPQ)EBC6787726(oapen)https://directory.doabooks.org/handle/20.500.12854/72797(PPN)258302194(ODN)ODN0010073849(oapen)doab72797(Au-PeEL)EBL6787726(OCoLC)1314627511(DE-He213)978-981-16-4095-7(EXLCZ)99534000000006837720211019d2022 u| 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierSublinear Computation Paradigm Algorithmic Revolution in the Big Data Era /edited by Naoki Katoh, Yuya Higashikawa, Hiro Ito, Atsuki Nagao, Tetsuo Shibuya, Adnan Sljoka, Kazuyuki Tanaka, Yushi Uno1st ed. 2022.Singapore :Springer Nature Singapore :Imprint: Springer,2022.1 online resource (403 p.)Computer Science SeriesDescription based upon print version of record.981-16-4094-7 Chapter 1: What is the Sublinear Computation Paradigm? -- Chapter 2: Property Testing on Graphs and Games -- Chapter 3: Constant-Time Algorithms for Continuous Optimization Problems -- Chapter 4: Oracle-based Primal-Dual Algorithms for Packing and Covering Semidefinite Programs -- Chapter 5: Almost Linear Time Algorithms for Some Problems on Dynamic Flow Networks -- Chapter 6: Sublinear Data Structure -- Chapter 7: Compression and Pattern Matching -- Chapter 8: Orthogonal Range Search Data Structures -- Chapter 9: Enhanced RAM Simulation in Succinct Space -- Chapter 10: Review of Sublinear Modeling in Markov Random Fields by Statistical-Mechanical Informatics and Statistical Machine Learning Theory -- Chapter 11: Empirical Bayes Method for Boltzmann Machines -- Chapter 12: Dynamical analysis of quantum annealing -- Chapter 13: Mean-field analysis of Sourlas codes with adiabatic reverse annealing -- Chapter 14: Rigidity theory for protein function analysis and structural accuracy validations -- Chapter 15: Optimization of Evacuating and Walking Home Routes from Osaka City with Big Road Network Data on Nankai Megathrust Earthquake -- Chapter 16: Stream-based Lossless Data Compression.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. 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.Computer Science SeriesComputer scienceAlgorithmsTheory of ComputationAlgorithmsComputer science.Algorithms.Theory of Computation.Algorithms.004.0151COM051300bisacshKatoh Naoki1238685Higashikawa Yuya1238686Ito Hiro1238687Nagao Atsuki1238688Shibuya Tetsuo1238689Sljoka Adnan1238690Tanaka Kazuyuki1238691Uno Yūshi0AU-PeELAU-PeELAU-PeELBOOK9910504285203321Sublinear Computation Paradigm2874616UNINA