High Dimensional Optimization And Probability

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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.

High Dimensional Optimization And Probability

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Author :
language : en
Publisher:
Release Date : 2022

High Dimensional Optimization And Probability written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Mathematical optimization 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.

High Dimensional Optimization

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Author : Jack Noonan
language : en
Publisher: Springer Nature
Release Date : 2024-05-31

High Dimensional Optimization written by Jack Noonan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Mathematics categories.

This book is interdisciplinary and unites several areas of applied probability, statistics, and computational mathematics including computer experiments, optimal experimental design, and global optimization. The bulk of the book is based on several recent papers by the authors but also contains new results. Considering applications, this brief highlights multistart and other methods of global optimizations requiring efficient exploration of the domain of optimization. This book is accessible to a wide range of readers; the prerequisites for reading the book are rather low, and many numerical examples are provided that pictorially illustrate the main ideas, methods, and conclusions. The main purpose of this book is the construction of efficient exploration strategies of high-dimensional sets. In high dimensions, the asymptotic arguments could be practically misleading and hence the emphasis on the non-asymptotic regime. An important link with global optimization stems from the observation that approximate covering is one of the key concepts associated with multistart and other key random search algorithms. In addition to global optimization, important applications of the results are computer experiments and machine learning. It is demonstrated that the asymptotically optimal space-filling designs, such as pure random sampling or low-discrepancy point nets, could be rather inefficient in the non-asymptotic regime and the authors suggest ways of increasing the efficiency of such designs. The range of techniques ranges from experimental design, Monte Carlo, and asymptotic expansions in the central limit theorem to multivariate geometry, theory of lattices, and numerical integration. This book could be useful to a wide circle of readers, especially those specializing in global optimization, numerical analysis, computer experiments, and computational mathematics. As specific recipes for improving set exploration schemes are formulated, the book can also be used by the practitioners interested in applications only.

Bayesian And High Dimensional Global Optimization

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Author : Anatoly Zhigljavsky
language : en
Publisher: Springer Nature
Release Date : 2021-03-02

Bayesian And High Dimensional Global Optimization written by Anatoly Zhigljavsky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-02 with Mathematics categories.

Accessible to a variety of readers, this book is of interest to specialists, graduate students and researchers in mathematics, optimization, computer science, operations research, management science, engineering and other applied areas interested in solving optimization problems. Basic principles, potential and boundaries of applicability of stochastic global optimization techniques are examined in this book. A variety of issues that face specialists in global optimization are explored, such as multidimensional spaces which are frequently ignored by researchers. The importance of precise interpretation of the mathematical results in assessments of optimization methods is demonstrated through examples of convergence in probability of random search. Methodological issues concerning construction and applicability of stochastic global optimization methods are discussed, including the one-step optimal average improvement method based on a statistical model of the objective function. A significant portion of this book is devoted to an analysis of high-dimensional global optimization problems and the so-called ‘curse of dimensionality’. An examination of the three different classes of high-dimensional optimization problems, the geometry of high-dimensional balls and cubes, very slow convergence of global random search algorithms in large-dimensional problems , and poor uniformity of the uniformly distributed sequences of points are included in this book.

Artificial Intelligence Methods For Optimization Of The Software Testing Process

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Author : Sahar Tahvili
language : en
Publisher: Academic Press
Release Date : 2022-07-21

Artificial Intelligence Methods For Optimization Of The Software Testing Process written by Sahar Tahvili and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-21 with Computers categories.

Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier's Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence - Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries - Explores specific comparative methodologies, focusing on developed and developing AI-based solutions - Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain - Explains all proposed solutions through real industrial case studies

Basal Ganglia X Proceedings Of The 10th Triennial Meeting Of The International Basal Ganglia Society

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Author : Charles J. Wilson
language : en
Publisher: Frontiers E-books
Release Date :

Basal Ganglia X Proceedings Of The 10th Triennial Meeting Of The International Basal Ganglia Society written by Charles J. Wilson and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

This volume contains articles describing research on the basic, pre-clinical and clinical neuroscience of the basal ganglia written by attendees of the 10th Triennial Meeting of the International Basal Ganglia Society (IBAGS) that was held June 20-24th, 2010 at the Ocean Place Resort in Long Branch, New Jersey, USA. For each of the preceding 9 IBAGS meetings, the meeting proceedings were published conventionally as a volume in the Advances in Behavioral Biology series. These volumes were expensive, were published only in very small quantities, had very limited availability to both basal ganglia researchers and the general neuroscience community, were not available on-line and the articles contained in each were not indexed in online searchable databases. Now, for the first time, IBAGS is taking full advantage of modern innovations in scientific publication and publishing IBAGS X as a Research Topics issue of Frontiers in Systems Neuroscience. The issue will be available on-line and is fully indexed by searchable databases including PubMed. Articles will include reports on the latest research on the anatomy and neurophysiology of single neurons and functional circuitry in the striatum, globus pallidus, subthalamic nucleus and substantia nigra as well as the latest data on animal models of basal ganglia dysfunction as well as behavioral and clinical studies in human patients.

High Dimensional Statistics

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Author : Martin J. Wainwright
language : en
Publisher: Cambridge University Press
Release Date : 2019-02-21

High Dimensional Statistics written by Martin J. Wainwright and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Business & Economics categories.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

Foundations Of Probability Theory

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Author : Himadri Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Foundations Of Probability Theory written by Himadri Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.

"Foundations of Probability Theory" offers a thorough exploration of probability theory's principles, methods, and applications. Designed for students, researchers, and practitioners, this comprehensive guide covers both foundational concepts and advanced topics. We begin with basic probability concepts, including sample spaces, events, probability distributions, and random variables, progressing to advanced topics like conditional probability, Bayes' theorem, and stochastic processes. This approach lays a solid foundation for further exploration. Our book balances theory and application, emphasizing practical applications and real-world examples. We cover topics such as statistical inference, estimation, hypothesis testing, Bayesian inference, Markov chains, Monte Carlo methods, and more. Each topic includes clear explanations, illustrative examples, and exercises to reinforce learning. Whether you're a student building a solid understanding of probability theory, a researcher exploring advanced topics, or a practitioner applying probabilistic methods to solve real-world problems, this book is an invaluable resource. We equip readers with the knowledge and tools necessary to tackle complex problems, make informed decisions, and explore probability theory's rich landscape with confidence.

Proceedings Of The 23rd Pacific Basin Nuclear Conference Volume 2

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Author : Chengmin Liu
language : en
Publisher: Springer Nature
Release Date : 2023-05-16

Proceedings Of The 23rd Pacific Basin Nuclear Conference Volume 2 written by Chengmin Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-16 with Science categories.

“This is the second in a series of three volumes of proceedings of the 23rd Pacific Basin Nuclear Conference (PBNC 2022) which was held by Chinese Nuclear Society. As one in the most important and influential conference series of nuclear science and technology, the 23rd PBNC was held in Beijing and Chengdu, China in 2022 with the theme “Nuclear Innovation for Zero-carbon Future”. For taking solid steps toward the goals of achieving peak carbon emissions and carbon neutrality, future-oriented nuclear energy should be developed in an innovative way for meeting global energy demands and coordinating the deployment mechanism. It brought together outstanding nuclear scientists and technical experts, senior industry executives, senior government officials and international energy organization leaders from all across the world. The proceedings highlight the latest scientific, technological and industrial advances in Nuclear Safety and Security, Operations and Maintenance, New Builds, Waste Management, Spent Fuel, Decommissioning, Supply Capability and Quality Management, Fuel Cycles, Digital Reactor and New Technology, Innovative Reactors and New Applications, Irradiation Effects, Public Acceptance and Education, Economics, Medical and Biological Applications, and also the student program that intends to raise students’ awareness in fully engaging in this career and keep them updated on the current situation and future trends. These proceedings are not only a good summary of the frontiers in nuclear science and technology, but also a useful guideline for the researchers, engineers and graduate students.

Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes

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Author : Cheng Few Lee
language : en
Publisher: World Scientific
Release Date : 2020-07-30

Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Business & Economics categories.

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.