Sparse Polynomial Approximation Of High Dimensional Functions


Sparse Polynomial Approximation Of High Dimensional Functions
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Sparse Polynomial Approximation Of High Dimensional Functions


Sparse Polynomial Approximation Of High Dimensional Functions
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Author : Ben Adcock
language : en
Publisher: SIAM
Release Date : 2022-02-16

Sparse Polynomial Approximation Of High Dimensional Functions written by Ben Adcock and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-16 with Mathematics categories.


Over seventy years ago, Richard Bellman coined the term “the curse of dimensionality” to describe phenomena and computational challenges that arise in high dimensions. These challenges, in tandem with the ubiquity of high-dimensional functions in real-world applications, have led to a lengthy, focused research effort on high-dimensional approximation—that is, the development of methods for approximating functions of many variables accurately and efficiently from data. This book provides an in-depth treatment of one of the latest installments in this long and ongoing story: sparse polynomial approximation methods. These methods have emerged as useful tools for various high-dimensional approximation tasks arising in a range of applications in computational science and engineering. It begins with a comprehensive overview of best s-term polynomial approximation theory for holomorphic, high-dimensional functions, as well as a detailed survey of applications to parametric differential equations. It then describes methods for computing sparse polynomial approximations, focusing on least squares and compressed sensing techniques. Sparse Polynomial Approximation of High-Dimensional Functions presents the first comprehensive and unified treatment of polynomial approximation techniques that can mitigate the curse of dimensionality in high-dimensional approximation, including least squares and compressed sensing. It develops main concepts in a mathematically rigorous manner, with full proofs given wherever possible, and it contains many numerical examples, each accompanied by downloadable code. The authors provide an extensive bibliography of over 350 relevant references, with an additional annotated bibliography available on the book’s companion website (www.sparse-hd-book.com). This text is aimed at graduate students, postdoctoral fellows, and researchers in mathematics, computer science, and engineering who are interested in high-dimensional polynomial approximation techniques.



High Dimensional Optimization And Probability


High Dimensional Optimization And Probability
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Author : Ashkan Nikeghbali
language : en
Publisher: Springer Nature
Release Date : 2022-08-04

High Dimensional Optimization And Probability written by Ashkan Nikeghbali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-04 with Mathematics categories.


This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability. Chapters also emphasize applications to Data Science, a timely field with a high impact in our modern society. The discussion presents modern, state-of-the-art, research results and advances in areas including non-convex optimization, decentralized distributed convex optimization, topics on surrogate-based reduced dimension global optimization in process systems engineering, the projection of a point onto a convex set, optimal sampling for learning sparse approximations in high dimensions, the split feasibility problem, higher order embeddings, codifferentials and quasidifferentials of the expectation of nonsmooth random integrands, adjoint circuit chains associated with a random walk, analysis of the trade-off between sample size and precision in truncated ordinary least squares, spatial deep learning, efficient location-based tracking for IoT devices using compressive sensing and machine learning techniques, and nonsmooth mathematical programs with vanishing constraints in Banach spaces. The book is a valuable source for graduate students as well as researchers working on Optimization, Probability and their various interconnections with a variety of other areas. Chapter 12 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.



Numerical Analysis Meets Machine Learning


Numerical Analysis Meets Machine Learning
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Author :
language : en
Publisher: Elsevier
Release Date : 2024-06-13

Numerical Analysis Meets Machine Learning written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-13 with Mathematics categories.


Numerical Analysis Meets Machine Learning series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Numerical Analysis series Updated release includes the latest information on the Numerical Analysis Meets Machine Learning



Sparse Polynomial Approximation Of High Dimensional Functions


Sparse Polynomial Approximation Of High Dimensional Functions
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Author : Ben Adcock
language : en
Publisher: Society for Industrial and Applied Mathematics (SIAM)
Release Date : 2021

Sparse Polynomial Approximation Of High Dimensional Functions written by Ben Adcock and has been published by Society for Industrial and Applied Mathematics (SIAM) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Approximation theory categories.


"This is a book about polynomial approximation in high dimensions"--



Compressed Sensing And Its Applications


Compressed Sensing And Its Applications
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Author : Holger Boche
language : en
Publisher: Birkhäuser
Release Date : 2018-01-17

Compressed Sensing And Its Applications written by Holger Boche and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-17 with Mathematics categories.


This contributed volume contains articles written by the plenary and invited speakers from the second international MATHEON Workshop 2015 that focus on applications of compressed sensing. Article authors address their techniques for solving the problems of compressed sensing, as well as connections to related areas like detecting community-like structures in graphs, curbatures on Grassmanians, and randomized tensor train singular value decompositions. Some of the novel applications covered include dimensionality reduction, information theory, random matrices, sparse approximation, and sparse recovery. This book is aimed at both graduate students and researchers in the areas of applied mathematics, computer science, and engineering, as well as other applied scientists exploring the potential applications for the novel methodology of compressed sensing. An introduction to the subject of compressed sensing is also provided for researchers interested in the field who are not as familiar with it.



Spectral And High Order Methods For Partial Differential Equations Icosahom 2018


Spectral And High Order Methods For Partial Differential Equations Icosahom 2018
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Author : Spencer J. Sherwin
language : en
Publisher: Springer Nature
Release Date : 2020-08-11

Spectral And High Order Methods For Partial Differential Equations Icosahom 2018 written by Spencer J. Sherwin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-11 with Mathematics categories.


This open access book features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions.



Advanced Reduced Order Methods And Applications In Computational Fluid Dynamics


Advanced Reduced Order Methods And Applications In Computational Fluid Dynamics
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Author : Gianluigi Rozza
language : en
Publisher: SIAM
Release Date : 2022-11-21

Advanced Reduced Order Methods And Applications In Computational Fluid Dynamics written by Gianluigi Rozza and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-21 with Mathematics categories.


Reduced order modeling is an important, growing field in computational science and engineering, and this is the first book to address the subject in relation to computational fluid dynamics. It focuses on complex parametrization of shapes for their optimization and includes recent developments in advanced topics such as turbulence, stability of flows, inverse problems, optimization, and flow control, as well as applications. This book will be of interest to researchers and graduate students in the field of reduced order modeling.



Mathematical Theory Of Finite Elements


Mathematical Theory Of Finite Elements
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Author : Leszek F. Demkowicz
language : en
Publisher: SIAM
Release Date : 2023-09-22

Mathematical Theory Of Finite Elements written by Leszek F. Demkowicz and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with Mathematics categories.


This book discusses the foundations of the mathematical theory of finite element methods. The focus is on two subjects: the concept of discrete stability, and the theory of conforming elements forming the exact sequence. Both coercive and noncoercive problems are discussed.. Following the historical path of development, the author covers the Ritz and Galerkin methods to Mikhlin’s theory, followed by the Lax–Milgram theorem and Cea’s lemma to the Babuska theorem and Brezzi’s theory. He finishes with an introduction to the discontinuous Petrov–Galerkin (DPG) method with optimal test functions. Based on the author’s personal lecture notes for a popular version of his graduate course on mathematical theory of finite elements, the book includes a unique exposition of the concept of discrete stability and the means to guarantee it, a coherent presentation of finite elements forming the exact grad-curl-div sequence, and an introduction to the DPG method. Intended for graduate students in computational science, engineering, and mathematics programs, Mathematical Theory of Finite Elements is also appropriate for graduate mathematics and mathematically oriented engineering students. Instructors will find the book useful for courses in real analysis, functional analysis, energy (Sobolev) spaces, and Hilbert space methods for PDEs.



A Ramble Through Probability


A Ramble Through Probability
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Author : Samopriya Basu
language : en
Publisher: SIAM
Release Date : 2024-03-06

A Ramble Through Probability written by Samopriya Basu and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-06 with Mathematics categories.


Measure theory and measure-theoretic probability are fascinating subjects. Proofs describing profound ways to reason lead to results that are frequently startling, beautiful, and useful. Measure theory and probability also play roles in the development of pure and applied mathematics, statistics, engineering, physics, and finance. Indeed, it is difficult to overstate their importance in the quantitative disciplines. This book traces an eclectic path through the fundamentals of the topic to make the material accessible to a broad range of students. A Ramble through Probability: How I Learned to Stop Worrying and Love Measure Theory brings together the key elements and applications in a unified presentation aimed at developing intuition; contains an extensive collection of examples that illustrate, explain, and apply the theories; and is supplemented with videos containing commentary and explanations of select proofs on an ancillary website. This book is intended for graduate students in engineering, mathematics, science, and statistics. Researchers who need to use probability theory will also find it useful. It is appropriate for graduate-level courses on measure theory and/or probability theory.



Quantification Of Uncertainty Improving Efficiency And Technology


Quantification Of Uncertainty Improving Efficiency And Technology
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Author : Marta D'Elia
language : en
Publisher: Springer Nature
Release Date : 2020-07-30

Quantification Of Uncertainty Improving Efficiency And Technology written by Marta D'Elia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Mathematics categories.


This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.