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Record Nr. |
UNINA9910574057803321 |
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Titolo |
Monte Carlo and Quasi-Monte Carlo Methods : MCQMC 2020, Oxford, United Kingdom, August 10–14 / / edited by Alexander Keller |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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9783030983192 |
9783030983185 |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (315 pages) |
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Collana |
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Springer Proceedings in Mathematics & Statistics, , 2194-1017 ; ; 387 |
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Disciplina |
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Soggetti |
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Statistics |
Number theory |
Functional analysis |
Mathematical optimization |
Number Theory |
Functional Analysis |
Optimization |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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 |
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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. |
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Sommario/riassunto |
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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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