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Monte Carlo and quasi-Monte Carlo methods = MCQMC 2016, Stanford, CA, August 14-19 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Monte Carlo and quasi-Monte Carlo methods/ edited by Art B. Owen, Peter W. Glynn.
其他題名:	MCQMC 2016, Stanford, CA, August 14-19 /
其他題名:	MCQMC 2016
其他作者:	Owen, Art B.
團體作者:	Workshop on the Preservation of Stability under Discretization
出版者:	Cham :Springer International Publishing : : 2018.,
面頁冊數:	xi, 479 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Monte Carlo method - Textbooks. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-91436-7
ISBN:	9783319914367

Monte Carlo and quasi-Monte Carlo methods = MCQMC 2016, Stanford, CA, August 14-19 /
Monte Carlo and quasi-Monte Carlo methodsMCQMC 2016, Stanford, CA, August 14-19 /[electronic resource] :MCQMC 2016edited by Art B. Owen, Peter W. Glynn. - Cham :Springer International Publishing :2018. - xi, 479 p. :ill. (some col.), digital ;24 cm. - Springer proceedings in mathematics & statistics,v.2412194-1009 ;. - Springer proceedings in mathematics & statistics ;v.24..

Part I Tutorials, Fred J. Hickernell, The Trio Identity for Quasi-Monte Carlo Error -- Pierre L'Ecuyer, Randomized Quasi-Monte Carlo: An Introduction for Practitioners -- Frances Y. Kuo and Dirk Nuyens, Application of Quasi-Monte Carlo Methods to PDEs with Random Coefﬁcients - an Overview and Tutorial -- Part II Invited talks, Jose Blanchet and Zhipeng Liu, Malliavin-based Multilevel Monte Carlo Estimators for Densities of Max-stable Processes -- Nicolas Chopin and Mathieu Gerber, Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes -- Frances Y. Kuo and Dirk Nuyens, Hot New Directions for Quasi-Monte Carlo Research in Step with Applications -- Saul Toscano-Palmerin and Peter I. Frazier, Stratiﬁed Bayesian Optimization -- Part III Regular talks, Christoph Aistleitner, Dmitriy Bilyk, and Aleksandar Nikolov, Tusnady's Problem, the Transference Principle, and Non-Uniform QMC Sampling -- Ken Dahm and Alexander Keller, Learning Light Transport the Reinforced Way -- Adrian Ebert, Hernan Leovey, and Dirk Nuyens, Successive Coordinate Search and Component-by-Component Construction of Rank-1 Lattice Rules -- Wei Fang and Michael B. Giles, Adaptive Euler-Maruyama method for SDEs with non-globally Lipschitz drift -- J. Feng and M. Huber and Y. Ruan, Monte Carlo with User-Speciﬁed Relative Error -- Robert N. Gantner, Dimension Truncation in QMC for Afﬁne-Parametric Operator Equations -- Michael B. Giles, Frances Y. Kuo, and Ian H. Sloan, Combining Sparse Grids, Multilevel MC and QMC for Elliptic PDEs with Random Coefﬁcients -- Hiroshi Haramoto and Makoto Matsumoto, A Method to Compute an Appropriate Sample Size of a Two-Level Test for the NIST Test Suite -- Stefan Heinrich, Lower Complexity Bounds for Parametric Stochastic Itoˆ Integration -- Lukas Herrmann and Christoph Schwab, QMC Algorithms with Product Weights for Lognormal-Parametric, Elliptic PDEs -- Masatake Hirao, QMC Designs and Determinantal Point Processes -- Adam W. Kolkiewicz, Efﬁcient Monte Carlo For Diffusion Processes Using Ornstein-Uhlenbeck Bridges -- Ralph Kritzinger, Optimal Discrepancy Rate of Point Sets in Besov Spaces with Negative Smoothness -- Ralph Kritzinger, Helene Laimer, and Mario Neumuller, A Reduced Fast Construction of Polynomial Lattice Point Sets with Low Weighted Star Discrepancy -- David Mandel and Giray Okten, Randomized Sobol' Sensitivity Indices -- Hisanari Otsu, Shinichi Kinuwaki, and Toshiya Hachisuka, Supervised Learning of How to Blend Light Transport Simulations -- Pieterjan Robbe, Dirk Nuyens, and Stefan Vandewalle, A Dimension-Adaptive Multi-Index Monte Carlo Method Applied to a Model of a Heat Exchanger -- Shuang Zhao, Rong Kong, and Jerome Spanier, Towards Real-Time Monte Carlo for Biomedicine -- Zeyu Zheng, Jose Blanchet, and Peter W. Glynn, Rates of Convergence and CLTs for Subcanonical Debiased MLMC.

This book presents the refereed proceedings of the Twelfth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at Stanford University (California) in August 2016. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising in particular, in finance, statistics, computer graphics and the solution of PDEs.

ISBN: 9783319914367

Standard No.: 10.1007/978-3-319-91436-7doiSubjects--Topical Terms:

744103
Monte Carlo method
--Textbooks.

LC Class. No.: QA298

Dewey Class. No.: 518.282

Monte Carlo and quasi-Monte Carlo methods = MCQMC 2016, Stanford, CA, August 14-19 /
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