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

Monte Carlo and Quasi-Monte Carlo Methods MCQMC 2016, Stanford, CA, August 14-19 / edited by Art B. Owen, Peter W. Glynn.

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...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Owen, Art B. (Editor), Glynn, Peter W. (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Springer Proceedings in Mathematics & Statistics, 241
Springer eBook Collection.
Subjects:
Computer simulation.
Computer mathematics.
Computer science—Mathematics.
Applied mathematics.
Engineering mathematics.
Statistics .
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 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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