High Dimensional Probability VIII: The Oaxaca Volume, Gozlan Nathael, Latala Rafal, Lounici Karim
Автор: Koch Название: Analysis of Multivariate and High-Dimensional Data ISBN: 0521887933 ISBN-13(EAN): 9780521887939 Издательство: Cambridge Academ Рейтинг: Цена: 10613.00 р. Наличие на складе: Поставка под заказ.
Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.
Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems.
Автор: Nathael Gozlan; Rafa? Lata?a; Karim Lounici; Moksh Название: High Dimensional Probability VIII ISBN: 3030263908 ISBN-13(EAN): 9783030263904 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matem?tica 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.
Автор: Christian Houdr?; David M. Mason; Jan Rosi?ski; Jo Название: High Dimensional Probability VI ISBN: 3034807996 ISBN-13(EAN): 9783034807999 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Houdr? Название: High Dimensional Probability VII ISBN: 3319405179 ISBN-13(EAN): 9783319405179 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'?tudes Scientifiques de Carg?se (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.
Автор: Houdrй Christian, Mason David M., Reynaud-Bouret Patricia Название: High Dimensional Probability VII: The Cargиse Volume ISBN: 3319821210 ISBN-13(EAN): 9783319821214 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Dedication to Evarist Gine-Masdeu.- Inequalities and Convexity.- Limit Theorems.- Stochastic Processes.- High Dimensional Statistics.
Автор: Joergen Hoffmann-Joergensen; Michael B. Marcus; Jo Название: High Dimensional Probability III ISBN: 3034894236 ISBN-13(EAN): 9783034894234 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Evarist Gin?; David M. Mason; Jon A. Wellner Название: High Dimensional Probability II ISBN: 1461271118 ISBN-13(EAN): 9781461271116 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Joergen Hoffmann-Joergensen; Michael B. Marcus; Jo Название: High Dimensional Probability III ISBN: 3764321873 ISBN-13(EAN): 9783764321871 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Giraud Название: Introduction to High-Dimensional Statistics ISBN: 1482237946 ISBN-13(EAN): 9781482237948 Издательство: Taylor&Francis Рейтинг: Цена: 9645.00 р. Наличие на складе: Нет в наличии.
Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.
Описание: This monograph is devoted to random walk based stochastic algorithms for solving high-dimensional boundary value problems of mathematical physics and chemistry. It includes Monte Carlo methods where the random walks live not only on the boundary, but also inside the domain. A variety of examples from capacitance calculations to electron dynamics in semiconductors are discussed to illustrate the viability of the approach.The book is written for mathematicians who work in the field of partial differential and integral equations, physicists and engineers dealing with computational methods and applied probability, for students and postgraduates studying mathematical physics and numerical mathematics. Contents: IntroductionRandom walk algorithms for solving integral equationsRandom walk-on-boundary algorithms for the Laplace equationWalk-on-boundary algorithms for the heat equationSpatial problems of elasticityVariants of the random walk on boundary for solving stationary potential problemsSplitting and survival probabilities in random walk methods and applicationsA random WOS-based KMC method for electron-hole recombinationsMonte Carlo methods for computing macromolecules properties and solving related problemsBibliography
Автор: Ernst Eberlein; Marjorie Hahn Название: High Dimensional Probability ISBN: 3034897901 ISBN-13(EAN): 9783034897907 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Roughly speaking, before 1970, the Gaussian processes that were studied were indexed by a subset of Euclidean space, mostly with dimension at most three. 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.
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