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Monte Carlo and Quasi-Monte Carlo Methods : MCQMC 2016, Stanford, CA, August 14-19

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概要 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 (Californi...a) 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.続きを見る
目次 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.
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本文を見る Full text available from Springer Mathematics and Statistics eBooks 2018 English/International

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登録日 2020.06.27
更新日 2020.06.28