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Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2020, Oxford, United Kingdom, August 10–14 de Alexander Keller

Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2020, Oxford, United Kingdom, August 10–14: Springer Proceedings in Mathematics & Statistics, cartea 387

Editat de Alexander Keller
en Limba Engleză Hardback – 21 mai 2022
This volume presents the revised papers of the 14th International Conference in Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, MCQMC 2020, which took place online during August 10-14, 2020. 
This book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in statistics, machine learning, finance, and computer graphics, offering information on the latest developments in Monte Carlo and quasi-Monte Carlo methods and their randomized versions.

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Specificații

ISBN-13: 9783030983185
ISBN-10: 3030983188
Pagini: 311
Ilustrații: XVI, 311 p. 69 illus., 53 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.59 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Springer Proceedings in Mathematics & Statistics

Locul publicării:Cham, Switzerland

Cuprins

The MCQMC Conference Series.- The MCQMC Conference Series: P. L’Ecuyer and F. Puchhammer, Density Estimation by Monte Carlo and Quasi-Monte Carlo.- Sou-Cheng T. Choi, Fred J. Hickernell, Rathinavel Jagadeeswaran, Michael J. McCourt, and Aleksei G. Sorokin, Quasi-Monte Carlo Software.- Part II Regular Talks: P. L’Ecuyer, P. Marion, M. Godin, and F. Puchhamme, A Tool for Custom Construction of QMC and RQMC Point Sets.- Art B. Owen, On Dropping the first Sobol’ Point.- C. Lemieux and J. Wiart, On the Distribution of Scrambled Nets over Unanchored Boxes.- S. Heinrich, Lower Bounds for the Number of Random Bits in Monte Carlo Algorithms.- N. Binder, S. Fricke, and A. Keller, Massively Parallel Path Space Filtering.- M. Hird, S. Livingstone, and G. Zanella, A fresh Take on ‘Barker Dynamics’ for MCMC.- P. Blondeel, P. Robbe, S. François, G. Lombaert and S. Vandewalle, On the Selection of Random Field Evaluation Points in the p-MLQMC Method.- S. Si, Chris. J. Oates, Andrew B. Duncan, L. Carin,and François-Xavier Briol, Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization.- Andrei S. Cozma and C. Reisinger, Simulation of Conditional Expectations under fast mean-reverting Stochastic Volatility Models.- M. Huber, Generating from the Strauss Process using stitching.- R. Nasdala and D. Potts, A Note on Transformed Fourier Systems for the Approximation of Non-Periodic Signals.- M. Hofert, A. Prasad, and Mu Zhu, Applications of Multivariate Quasi-Random Sampling with Neural Networks.- A. Keller and Matthijs Van keirsbilck, Artificial Neural Networks generated by Low Discrepancy Sequences.

Textul de pe ultima copertă

This volume presents the revised papers of the 14th International Conference in Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, MCQMC 2020, which took place online during August 10-14, 2020. 
This book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in statistics, machine learning, finance, and computer graphics, offering information on the latest developments in Monte Carlo and quasi-Monte Carlo methods and their randomized versions.

Caracteristici

Includes proceedings of MCQMC 2020 Provides major source of information for Monte Carlo and quasi-Monte Carlo researchers Acts as excellent reference resource in solving high-dimensional computational problems