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Libros sobre el tema "Stochastic second order methods"

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Publicado: 1 de junio de 2024
Última modificación: 31 de julio de 2025

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1

Lan, Guanghui. First-order and Stochastic Optimization Methods for Machine Learning. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39568-1.

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2

Shepherd, Adrian J. Second-Order Methods for Neural Networks. Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0953-2.

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3

Strassert, Günter. The balancing principle, strict superiority relations, and a transitive overall final order of options. Institut für Regionalwissenschaft der Universität Karlsruhe, 2000.

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4

Otmani, Zoulikha Zaidi ep. Numerical methods for second order parabolic partial differential equations. Brunel University, 1986.

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5

Aamir, Shabbir, and United States. National Aeronautics and Space Administration., eds. Methods of ensuring realizability for non-realizable second order closures. National Aeronautics and Space Administration, 1994.

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6

Shepherd, Adrian J. Second-order methods for neural networks: Fast and reliable training methods for multi-layer perceptrons. Springer, 1997.

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7

Krispin, J. Second-order Godunov methods and self-similar steady supersonic three-dimensional flowfields. American Institute of Aeronautics and Astronautics, 1991.

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8

Heinrich, Bernd. Finite difference methods on irregular networks: A generalized approach to second order elliptic problems. Akademie-Verlag, 1987.

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9

Heinrich, Bernd. Finite difference methods on irregular networks: A generalized approach to second order elliptic problems. Birkhäuser Verlag, 1987.

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10

International Conference on Spectral and High Order Methods (2nd 1992 Montpellier, France). ICOSAHOM'92: Selected papers from the second International Conference on Spectral and High Order Methods, Montpellier, France, 22-26 June 1992. North-Holland, 1994.

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11

1943-, Gossez J. P., and Bonheure Denis, eds. Nonlinear elliptic partial differential equations: Workshop in celebration of Jean-Pierre Gossez's 65th birthday, September 2-4, 2009, Université libre de Bruxelles, Belgium. American Mathematical Society, 2011.

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12

Chemodurov, Vladimir, and Ella Litvinova. Physical and mathematical modeling of building systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1014191.

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Physical and mathematical modeling is widely used in scientific research. This is due to the fact that field experiments on real construction sites are often impossible to organize for various reasons. The material included in the textbook is a summary of the authors ' experience in the field of system analysis. In the first section, the regularities of physical modeling of the functioning of objects based on the similarity and dimension theorems are considered. The second section presents modern models and methods for choosing optimal solutions: linear, nonlinear, stochastic, and statistical.
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13

Sequeira, A., H. Beirão da Veiga, and V. A. Solonnikov. Recent advances in partial differential equations and applications: International conference in honor of Hugo Beirao de Veiga's 70th birthday, February 17-214, 2014, Levico Terme (Trento), Italy. Edited by Rădulescu, Vicenţiu D., 1958- editor. American Mathematical Society, 2016.

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14

Zhukova, Galina. Differential equations. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1072180.

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The textbook presents the theory of ordinary differential equations constituting the subject of the discipline "Differential equations". Studied topics: differential equations of first, second, arbitrary order; differential equations; integration of initial and boundary value problems; stability theory of solutions of differential equations and systems. Introduced the basic concepts, proven properties of differential equations and systems. The article presents methods of analysis and solutions. We consider the applications of the obtained results, which are illustrated on a large number of spe
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15

Multidimensional second order stochastic processes. World Scientific, 1997.

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16

Multidimensional Second Order Stochastic Processes. World Scientific Publishing Co Pte Ltd, 1997.

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17

Multidimensional Second Order Stochastic Processes. World Scientific Publishing Co Pte Ltd, 1997.

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18

Lan, Guanghui. First-Order and Stochastic Optimization Methods for Machine Learning. Springer International Publishing AG, 2021.

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19

Lan, Guanghui. First-order and Stochastic Optimization Methods for Machine Learning. Springer, 2020.

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20

First-order and Stochastic Optimization Methods for Machine Learning. Springer Nature, 2020.

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21

Shepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer, 2014.

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22

Shepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer London, Limited, 2012.

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23

Mitchell, Andrew. Second-order Learning in Developmental Evaluation: New Methods for Complex Conditions. Palgrave Pivot, 2018.

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24

Mitchell, Andrew. Second-order Learning in Developmental Evaluation: New Methods for Complex Conditions. Palgrave Pivot, 2018.

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25

Gaivoronski, Alexei A., Pavel S. Knopov, Vladimir I. Norkin, and Volodymyr A. Zaslavskyi. Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection 2: Methods and Tools. ISTE-Wiley, 2025. https://doi.org/10.1115/1.862smo.

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Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection is a thorough exploration of mathematical models and tools that are designed to strengthen critical infrastructures against threats – both natural and adversarial. Divided into two volumes, this first volume examines stochastic modeling across key economic sectors and their interconnections, while the second volume focuses on advanced mathematical methods for enhancing infrastructure protection. The book covers a range of themes, including risk assessment techniques that account for systemic interdependencies w
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26

Chen, Nan. Stochastic Methods for Modeling and Predicting Complex Dynamical Systems: Uncertainty Quantification, State Estimation, and Reduced-Order Models. Springer International Publishing AG, 2023.

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27

Finite Difference Methods on Irregular Networks: A Generalized Approach to Second Order Elliptic Problems. de Gruyter GmbH, Walter, 1987.

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28

Finite Difference Methods on Irregular Networks: A Generalized Approach to Second Order Elliptic Problems. de Gruyter GmbH, Walter, 1987.

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29

Scan Statistics: Methods and Applications. Springer London, Limited, 2009.

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30

Wang, Junping. Asymptotic expansions and L [infinity symbol]-error estimates for mixed finite element methods for second order elliptic problems. 1988.

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31

Edmunds, D. E., and W. D. Evans. Second-Order Differential Operators on Arbitrary Open Sets. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198812050.003.0007.

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In this chapter, three different methods are described for obtaining nice operators generated in some L2 space by second-order differential expressions and either Dirichlet or Neumann boundary conditions. The first is based on sesquilinear forms and the determination of m-sectorial operators by Kato’s First Representation Theorem; the second produces an m-accretive realization by a technique due to Kato using his distributional inequality; the third has its roots in the work of Levinson and Titchmarsh and gives operators T that are such that iT is m-accretive. The class of such operators inclu
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32

Felix, Isaac. Class of P-Stable Hybrid Linear Multistep Methods with Minimal Phase-Lag Error for Second Order Initial Value Problems. GRIN Verlag GmbH, 2018.

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33

Heinrich, Bernd. Finite Difference Methods on Irregular Networks: A Generalized Approach to Second Order Elliptic Problems (Intl Series Numerical Mathematic, Vol 82). Birkhauser, 1988.

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34

Implementing Families of Implicit Chebyshev Methods with Exact Coefficients for the Numerical Integration of First- and Second-Order Differential Equations. Storming Media, 2002.

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35

Advances in Distribution Theory, Order Statistics, and Inference (Statistics for Industry and Technology). Birkhäuser Boston, 2007.

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36

Fokker-Planck-Kolmogorov equations. American Mathematical Society, 2015.

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37

Krylov, Nicolai V., Michael Rockner, Vladimir I. Bogachev, and Stanislav V. Shaposhnikov. Fokker-Planck-Kolmogorov Equations. American Mathematical Society, 2015.

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38

Ratner, Bruce. Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. Taylor & Francis Group, 2013.

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39

Anonyma. Medical Pocket-Book: Containing a Short but Plain Account of the Symptoms, Causes, and Methods of Cure, of the Diseases Incident to the Human Body... . Extracted from the Best Authors, and Digested into Alphabetical Order. the Second Edition,. Creative Media Partners, LLC, 2023.

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40

Anonyma. Medical Pocket-Book: Containing a Short but Plain Account of the Symptoms, Causes, and Methods of Cure, of the Diseases Incident to the Human Body... . Extracted from the Best Authors, and Digested into Alphabetical Order. the Second Edition,. Creative Media Partners, LLC, 2023.

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41

Glaz, Joseph, Joseph Naus, and Sylvan Wallenstein. Scan Statistics. Springer London, Limited, 2013.

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42

Scan Statistics (Springer Series in Statistics). Springer, 2001.

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43

Kubek, Maria M., and Zhong Li, eds. Autonomous Systems 2018. VDI Verlag, 2018. http://dx.doi.org/10.51202/9783186862105.

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To meet the expectations raised by the terms Industry 4.0, Industrial Internet and Internet of Things, real innovations are necessary, which can be brought about by information processing systems working autonomously. Owing to their growing complexity and their embedding in ever-changing environments, their design becomes increasingly critical. Thus, the many topics addressed in this book range from data integration on hardware level to methods for security and safety of data and to stochastic methods, data interferences as well as machine learning and search in decentralised systems. Their va
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44

Spectral analysis, differential equations, and mathematical physics: A festschrift in honor of Fritz Gesztesy's 60th birthday. American Mathematical Society, 2013.

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45

Nitzan, Abraham. Chemical Dynamics in Condensed Phases. Oxford University PressOxford, 2024. http://dx.doi.org/10.1093/9780191947971.001.0001.

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Abstract This second edition builds on the first, providing a uniform approach to diverse problems encountered in the study of dynamical processes in condensed-phase molecular systems. It focuses on three themes: coverage of needed background material, in-depth introduction of methodologies, and analysis of several key applications to processes of importance in physical, chemical and biological phenomena in complex systems. Chapter 1 starts with a general review of basic mathematical and physical methods. It is followed by a few introductory chapters on quantum dynamics (Chapter 2), radiation–
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46

Nitzan, Abraham. Chemical Dynamics in Condensed Phases. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780198529798.001.0001.

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This text provides a uniform and consistent approach to diversified problems encountered in the study of dynamical processes in condensed phase molecular systems. Given the broad interdisciplinary aspect of this subject, the book focuses on three themes: coverage of needed background material, in-depth introduction of methodologies, and analysis of several key applications. The uniform approach and common language used in all discussions help to develop general understanding and insight on condensed phases chemical dynamics. The applications discussed are among the most fundamental processes t
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47

Henriksen, Niels E., and Flemming Y. Hansen. Theories of Molecular Reaction Dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805014.001.0001.

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This book deals with a central topic at the interface of chemistry and physics—the understanding of how the transformation of matter takes place at the atomic level. Building on the laws of physics, the book focuses on the theoretical framework for predicting the outcome of chemical reactions. The style is highly systematic with attention to basic concepts and clarity of presentation. Molecular reaction dynamics is about the detailed atomic-level description of chemical reactions. Based on quantum mechanics and statistical mechanics or, as an approximation, classical mechanics, the dynamics of
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48

Lopes, Dominic McIver. Aesthetics in Three Dimensions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198796657.003.0002.

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This chapter begins with a historical overview of aesthetics and the philosophy of art before turning to a discussion of how the philosophy of art bears upon human culture. It then considers the methods used in attacking problems in aesthetics and the philosophy of art by highlighting the distinctions between pure and applied philosophy, between internal and external perspectives on aesthetic and artistic phenomena, and between first-order and second-order methods. It also examines how aesthetics and the philosophy of art are affected as the arts evolve and as empirical studies of aesthetic an
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49

Lopes, Dominic McIver. Aesthetics and Philosophy of Art. Edited by Herman Cappelen, Tamar Szabó Gendler, and John Hawthorne. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199668779.013.11.

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This article focuses on aesthetics and the philosophy of art as branches of so-called analytic philosophy. It begins with a historical overview of aesthetics and the philosophy of art before turning to a discussion of how the philosophy of art bears upon human culture. It then considers the methods used in attacking problems in aesthetics and the philosophy of art by highlighting the distinctions between pure and applied philosophy, between internal and external perspectives on aesthetic and artistic phenomena, and between first-order and second-order methods. It also examines how aesthetics a
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50

Ross, John, Igor Schreiber, and Marcel O. Vlad. Determination of Complex Reaction Mechanisms. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195178685.001.0001.

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In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathw
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