High Dimensional Probability IX

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Publisher : Springer Nature
ISBN 13 : 3031269799
Total Pages : 445 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis High Dimensional Probability IX by : Radosław Adamczak

Download or read book High Dimensional Probability IX written by Radosław Adamczak and published by Springer Nature. This book was released on 2023-06-05 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects selected papers from the Ninth High Dimensional Probability Conference, held virtually from June 15-19, 2020. These papers cover a wide range of topics and demonstrate how high-dimensional probability remains an active area of research with applications across many mathematical disciplines. Chapters are organized around four general topics: inequalities and convexity; limit theorems; stochastic processes; and high-dimensional statistics. High Dimensional Probability IX will be a valuable resource for researchers in this area.

High Dimensional Probability

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Publisher : IMS
ISBN 13 : 9780940600676
Total Pages : 288 pages
Book Rating : 4.6/5 (6 download)

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Book Synopsis High Dimensional Probability by : Evarist Giné

Download or read book High Dimensional Probability written by Evarist Giné and published by IMS. This book was released on 2006 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:

High-Dimensional Probability

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Publisher : Cambridge University Press
ISBN 13 : 1108244548
Total Pages : 299 pages
Book Rating : 4.1/5 (82 download)

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Book Synopsis High-Dimensional Probability by : Roman Vershynin

Download or read book High-Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate theory, key tools, and modern applications of high-dimensional probability. Concentration inequalities form the core, and it covers both classical results such as Hoeffding's and Chernoff's inequalities and modern developments such as the matrix Bernstein's inequality. It then introduces the powerful methods based on stochastic processes, including such tools as Slepian's, Sudakov's, and Dudley's inequalities, as well as generic chaining and bounds based on VC dimension. A broad range of illustrations is embedded throughout, including classical and modern results for covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, machine learning, compressed sensing, and sparse regression.

High Dimensional Probability II

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Publisher : Springer Science & Business Media
ISBN 13 : 1461213584
Total Pages : 491 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis High Dimensional Probability II by : Evarist Giné

Download or read book High Dimensional Probability II written by Evarist Giné and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: High dimensional probability, in the sense that encompasses the topics rep resented in this volume, began about thirty years ago with research in two related areas: limit theorems for sums of independent Banach space valued random vectors and general Gaussian processes. An important feature in these past research studies has been the fact that they highlighted the es sential probabilistic nature of the problems considered. In part, this was because, by working on a general Banach space, one had to discard the extra, and often extraneous, structure imposed by random variables taking values in a Euclidean space, or by processes being indexed by sets in R or Rd. Doing this led to striking advances, particularly in Gaussian process theory. It also led to the creation or introduction of powerful new tools, such as randomization, decoupling, moment and exponential inequalities, chaining, isoperimetry and concentration of measure, which apply to areas well beyond those for which they were created. The general theory of em pirical processes, with its vast applications in statistics, the study of local times of Markov processes, certain problems in harmonic analysis, and the general theory of stochastic processes are just several of the broad areas in which Gaussian process techniques and techniques from probability in Banach spaces have made a substantial impact. Parallel to this work on probability in Banach spaces, classical proba bility and empirical process theory were enriched by the development of powerful results in strong approximations.

High Dimensional Probability VI

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Publisher : Springer Science & Business Media
ISBN 13 : 3034804903
Total Pages : 374 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis High Dimensional Probability VI by : Christian Houdré

Download or read book High Dimensional Probability VI written by Christian Houdré and published by Springer Science & Business Media. This book was released on 2013-04-19 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of papers by participants at High Dimensional Probability VI Meeting held from October 9-14, 2011 at the Banff International Research Station in Banff, Alberta, Canada. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other areas of mathematics, statistics, and computer science. These include random matrix theory, nonparametric statistics, empirical process theory, statistical learning theory, concentration of measure phenomena, strong and weak approximations, distribution function estimation in high dimensions, combinatorial optimization, and random graph theory. The papers in this volume show that HDP theory continues to develop new tools, methods, techniques and perspectives to analyze the random phenomena. Both researchers and advanced students will find this book of great use for learning about new avenues of research.​

High Dimensional Probability

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Publisher : Birkhäuser
ISBN 13 : 3034888295
Total Pages : 336 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis High Dimensional Probability by : Ernst Eberlein

Download or read book High Dimensional Probability written by Ernst Eberlein and published by Birkhäuser. This book was released on 2012-12-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is high dimensional probability? Under this broad name we collect topics with a common philosophy, where the idea of high dimension plays a key role, either in the problem or in the methods by which it is approached. Let us give a specific example that can be immediately understood, that of Gaussian processes. Roughly speaking, before 1970, the Gaussian processes that were studied were indexed by a subset of Euclidean space, mostly with dimension at most three. Assuming some regularity on the covariance, one tried to take advantage of the structure of the index set. Around 1970 it was understood, in particular by Dudley, Feldman, Gross, and Segal that a more abstract and intrinsic point of view was much more fruitful. The index set was no longer considered as a subset of Euclidean space, but simply as a metric space with the metric canonically induced by the process. This shift in perspective subsequently lead to a considerable clarification of many aspects of Gaussian process theory, and also to its applications in other settings.

High Dimensional Probability III

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Publisher : Birkhäuser
ISBN 13 : 3034880596
Total Pages : 346 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis High Dimensional Probability III by : Joergen Hoffmann-Joergensen

Download or read book High Dimensional Probability III written by Joergen Hoffmann-Joergensen and published by Birkhäuser. This book was released on 2012-12-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: The title High Dimensional Probability is used to describe the many tributaries of research on Gaussian processes and probability in Banach spaces that started in the early 1970s. Many of the problems that motivated researchers at that time were solved. But the powerful new tools created for their solution turned out to be applicable to other important areas of probability. They led to significant advances in the study of empirical processes and other topics in theoretical statistics and to a new approach to the study of aspects of Lévy processes and Markov processes in general. The papers in this book reflect these broad categories. The volume thus will be a valuable resource for postgraduates and reseachers in probability theory and mathematical statistics.

High Dimensional Probability III

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Publisher : Birkhauser
ISBN 13 : 9780817621872
Total Pages : 346 pages
Book Rating : 4.6/5 (218 download)

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Book Synopsis High Dimensional Probability III by : Jørgen Hoffmann-Jørgensen

Download or read book High Dimensional Probability III written by Jørgen Hoffmann-Jørgensen and published by Birkhauser. This book was released on 2003 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt:

High Dimensional Probability VII

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Publisher : Birkhäuser
ISBN 13 : 3319405195
Total Pages : 480 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis High Dimensional Probability VII by : Christian Houdré

Download or read book High Dimensional Probability VII written by Christian Houdré and published by Birkhäuser. This book was released on 2016-09-21 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (IESC) in Corsica, France. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

High Dimensional Probability VIII

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Publisher : Springer Nature
ISBN 13 : 3030263916
Total Pages : 457 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis High Dimensional Probability VIII by : Nathael Gozlan

Download or read book High Dimensional Probability VIII written by Nathael Gozlan and published by Springer Nature. This book was released on 2019-11-26 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matemática Oaxaca (CMO), Mexico. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, random graphs, information theory and convex geometry. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

High Dimensional Probability

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Publisher :
ISBN 13 :
Total Pages : 275 pages
Book Rating : 4.:/5 (32 download)

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Book Synopsis High Dimensional Probability by :

Download or read book High Dimensional Probability written by and published by . This book was released on 2008* with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This e-book is the product of Project Euclid and its mission to advance scholarly communication in the field of theoretical and applied mathematics and statistics. Project Euclid was developed and deployed by the Cornell University Library and is jointly managed by Cornell and the Duke University Press.

High-Dimensional Statistics

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Publisher : Cambridge University Press
ISBN 13 : 1108498027
Total Pages : 571 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis High-Dimensional Statistics by : Martin J. Wainwright

Download or read book High-Dimensional Statistics written by Martin J. Wainwright and published by Cambridge University Press. This book was released on 2019-02-21 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

High Dimensional Probability V

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Publisher :
ISBN 13 : 9780940600782
Total Pages : 356 pages
Book Rating : 4.6/5 (7 download)

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Book Synopsis High Dimensional Probability V by : David M. Mason

Download or read book High Dimensional Probability V written by David M. Mason and published by . This book was released on 2009 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Uncertainty Analysis with High Dimensional Dependence Modelling

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Publisher : John Wiley & Sons
ISBN 13 : 0470863080
Total Pages : 302 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Uncertainty Analysis with High Dimensional Dependence Modelling by : Dorota Kurowicka

Download or read book Uncertainty Analysis with High Dimensional Dependence Modelling written by Dorota Kurowicka and published by John Wiley & Sons. This book was released on 2006-10-02 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Uncertainty analysis aims to quantify the overall uncertainty within a model, in order to support problem owners in model-based decision-making. In recent years there has been an explosion of interest in uncertainty analysis. Uncertainty and dependence elicitation, dependence modelling, model inference, efficient sampling, screening and sensitivity analysis, and probabilistic inversion are among the active research areas. This text provides both the mathematical foundations and practical applications in this rapidly expanding area, including: An up-to-date, comprehensive overview of the foundations and applications of uncertainty analysis. All the key topics, including uncertainty elicitation, dependence modelling, sensitivity analysis and probabilistic inversion. Numerous worked examples and applications. Workbook problems, enabling use for teaching. Software support for the examples, using UNICORN - a Windows-based uncertainty modelling package developed by the authors. A website featuring a version of the UNICORN software tailored specifically for the book, as well as computer programs and data sets to support the examples. Uncertainty Analysis with High Dimensional Dependence Modelling offers a comprehensive exploration of a new emerging field. It will prove an invaluable text for researches, practitioners and graduate students in areas ranging from statistics and engineering to reliability and environmetrics.

Statistical Analysis for High-Dimensional Data

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Publisher : Springer
ISBN 13 : 3319270990
Total Pages : 306 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Statistical Analysis for High-Dimensional Data by : Arnoldo Frigessi

Download or read book Statistical Analysis for High-Dimensional Data written by Arnoldo Frigessi and published by Springer. This book was released on 2016-02-16 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

Basics of Modern Mathematical Statistics

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Publisher : Springer
ISBN 13 : 3642399096
Total Pages : 311 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Basics of Modern Mathematical Statistics by : Vladimir Spokoiny

Download or read book Basics of Modern Mathematical Statistics written by Vladimir Spokoiny and published by Springer. This book was released on 2014-10-25 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a unified and self-contained presentation of the main approaches to and ideas of mathematical statistics. It collects the basic mathematical ideas and tools needed as a basis for more serious study or even independent research in statistics. The majority of existing textbooks in mathematical statistics follow the classical asymptotic framework. Yet, as modern statistics has changed rapidly in recent years, new methods and approaches have appeared. The emphasis is on finite sample behavior, large parameter dimensions, and model misspecifications. The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics. This textbook is primarily intended for graduate and postdoc students and young researchers who are interested in modern statistical methods.

Handbook of Computational Finance

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Publisher : Springer Science & Business Media
ISBN 13 : 3642172547
Total Pages : 791 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Handbook of Computational Finance by : Jin-Chuan Duan

Download or read book Handbook of Computational Finance written by Jin-Chuan Duan and published by Springer Science & Business Media. This book was released on 2011-10-25 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.