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Author: Mikhail Lifshits
Publisher: Springer Science & Business Media
ISBN: 3642249388
Category : Mathematics
Languages : en
Pages : 129
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Book Description
Gaussian processes can be viewed as a far-reaching infinite-dimensional extension of classical normal random variables. Their theory presents a powerful range of tools for probabilistic modelling in various academic and technical domains such as Statistics, Forecasting, Finance, Information Transmission, Machine Learning - to mention just a few. The objective of these Briefs is to present a quick and condensed treatment of the core theory that a reader must understand in order to make his own independent contributions. The primary intended readership are PhD/Masters students and researchers working in pure or applied mathematics. The first chapters introduce essentials of the classical theory of Gaussian processes and measures with the core notions of reproducing kernel, integral representation, isoperimetric property, large deviation principle. The brevity being a priority for teaching and learning purposes, certain technical details and proofs are omitted. The later chapters touch important recent issues not sufficiently reflected in the literature, such as small deviations, expansions, and quantization of processes. In university teaching, one can build a one-semester advanced course upon these Briefs.
Author: Mikhail Lifshits
Publisher: Springer Science & Business Media
ISBN: 3642249388
Category : Mathematics
Languages : en
Pages : 129
Get Book Here
Book Description
Gaussian processes can be viewed as a far-reaching infinite-dimensional extension of classical normal random variables. Their theory presents a powerful range of tools for probabilistic modelling in various academic and technical domains such as Statistics, Forecasting, Finance, Information Transmission, Machine Learning - to mention just a few. The objective of these Briefs is to present a quick and condensed treatment of the core theory that a reader must understand in order to make his own independent contributions. The primary intended readership are PhD/Masters students and researchers working in pure or applied mathematics. The first chapters introduce essentials of the classical theory of Gaussian processes and measures with the core notions of reproducing kernel, integral representation, isoperimetric property, large deviation principle. The brevity being a priority for teaching and learning purposes, certain technical details and proofs are omitted. The later chapters touch important recent issues not sufficiently reflected in the literature, such as small deviations, expansions, and quantization of processes. In university teaching, one can build a one-semester advanced course upon these Briefs.
Author: Vladimir Ilich Piterbarg
Publisher:
ISBN: 9780984422197
Category : Mathematics
Languages : en
Pages : 182
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Book Description
"Twenty Lectures ..." is based on a course that Professor Piterbarg, a founder of the asymptotic theory of Gaussian processes and fields, teaches to higher-level undergraduate and graduate students at the Faculty of Mechanics and Mathematics, Lomonosov Moscow State University. Written in a clear and succinct style, the book provides a wide-ranging introduction to the field. The first half of the book is devoted to the general theory of Gaussian distributions in both finite- and infinite-dimensional vector spaces. Fundamental results, such as Slepian's, Fernique-Sudakov's and Berman's inequalities, among many others, are clearly explained from a modern, unified point of view. The second half of the book focuses on asymptotic methods, in particular on distributions of high extrema of Gaussian processes and fields. Foundational tools such as the Double Sum Method, the Method of Moments, and the Comparison Method, invented and popularized by the author, are prominently featured. This part adapts material from Professor Piterbarg's famous monograph to make it more accessible to a wider audience. No previous knowledge of stochastic processes is assumed, as all results are derived from a few basic facts of calculus and functional analysis. Written by a world-renowned expert in the field, "Twenty Lectures ..." is a must-read for students and experienced researchers alike - or anyone with an interest in Gaussian processes and fields. The text provides an excellent basis for a full-length graduate course. Albert N. Shiryaev, Member of the Russian Academy of Sciences, Chair of the Department of Probability Theory, Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, says: "Professor Piterbarg's lectures are finally available in English and there is simply no other book on the subject that compares. Having contributed so much to the development of the asymptotic theory of Gaussian processes, the author manages to keep his lectures accessible yet rigorous. The lectures cover such a wide range of results and tools that this book is absolutely indispensable to anyone with an interest in the subject."
Author: Jean-Marc Azais
Publisher: John Wiley & Sons
ISBN: 0470434635
Category : Mathematics
Languages : en
Pages : 407
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Book Description
A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics are provided, specifically to systems of random equations and condition numbers of random matrices. Throughout the book, applications are illustrated from various areas of study such as statistics, genomics, and oceanography while other results are relevant to econometrics, engineering, and mathematical physics. The presented material is reinforced by end-of-chapter exercises that range in varying degrees of difficulty. Most fundamental topics are addressed in the book, and an extensive, up-to-date bibliography directs readers to existing literature for further study. Level Sets and Extrema of Random Processes and Fields is an excellent book for courses on probability theory, spatial statistics, Gaussian fields, and probabilistic methods in real computation at the upper-undergraduate and graduate levels. It is also a valuable reference for professionals in mathematics and applied fields such as statistics, engineering, econometrics, mathematical physics, and biology.
Author: Roland Dobrushin
Publisher: Springer
ISBN: 3540496351
Category : Mathematics
Languages : en
Pages : 308
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Book Description
Author: Carl Edward Rasmussen
Publisher: MIT Press
ISBN: 026218253X
Category : Computers
Languages : en
Pages : 266
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Book Description
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
Author: Martin T. Barlow
Publisher: Springer Nature
ISBN: 3030320111
Category : Mathematics
Languages : en
Pages : 421
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Book Description
The 2017 PIMS-CRM Summer School in Probability was held at the Pacific Institute for the Mathematical Sciences (PIMS) at the University of British Columbia in Vancouver, Canada, during June 5-30, 2017. It had 125 participants from 20 different countries, and featured two main courses, three mini-courses, and twenty-nine lectures. The lecture notes contained in this volume provide introductory accounts of three of the most active and fascinating areas of research in modern probability theory, especially designed for graduate students entering research: Scaling limits of random trees and random graphs (Christina Goldschmidt) Lectures on the Ising and Potts models on the hypercubic lattice (Hugo Duminil-Copin) Extrema of the two-dimensional discrete Gaussian free field (Marek Biskup) Each of these contributions provides a thorough introduction that will be of value to beginners and experts alike.
Author: Catherine Donati-Martin
Publisher: Springer
ISBN: 3319444654
Category : Mathematics
Languages : en
Pages : 503
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Book Description
In addition to its further exploration of the subject of peacocks, introduced in recent Séminaires de Probabilités, this volume continues the series’ focus on current research themes in traditional topics such as stochastic calculus, filtrations and random matrices. Also included are some particularly interesting articles involving harmonic measures, random fields and loop soups. The featured contributors are Mathias Beiglböck, Martin Huesmann and Florian Stebegg, Nicolas Juillet, Gilles Pags, Dai Taguchi, Alexis Devulder, Mátyás Barczy and Peter Kern, I. Bailleul, Jürgen Angst and Camille Tardif, Nicolas Privault, Anita Behme, Alexander Lindner and Makoto Maejima, Cédric Lecouvey and Kilian Raschel, Christophe Profeta and Thomas Simon, O. Khorunzhiy and Songzi Li, Franck Maunoury, Stéphane Laurent, Anna Aksamit and Libo Li, David Applebaum, and Wendelin Werner.
Author: N. H. Bingham
Publisher: Cambridge University Press
ISBN: 9780521379434
Category : Mathematics
Languages : en
Pages : 518
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Book Description
A comprehensive account of the theory and applications of regular variation.
Author: Shashi Shekhar
Publisher: Springer Science & Business Media
ISBN: 038730858X
Category : Computers
Languages : en
Pages : 1392
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Book Description
The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.
Author: Hui Liu
Publisher: Springer Nature
ISBN: 9811518602
Category : Technology & Engineering
Languages : en
Pages : 288
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Book Description
Focusing on non-intrusive load monitoring techniques in the area of smart grids and smart buildings, this book presents a thorough introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load monitoring techniques are highly promising in terms of their energy-saving and carbon emission reduction potential. The book is structured clearly and written concisely. It introduces each aspect of these techniques with a number of examples, helping readers to understand and use the corresponding results. It provides latest strengths on the non-intrusive load monitoring techniques for engineers and managers of relevant departments. It also offers extensive information and a source of inspiration for researchers and students, while outlining future research directions.
