High-Dimensional Optimization and Probability With a View Towards Data Science

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...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Nikeghbali, Ashkan, editor (editor), Pardalos, Panos M., editor, Raigorodskii, Andrei M., editor, Rassias, Michael Th., editor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cham : Springer International Publishing 2022.
Edición:1st ed
Colección:Springer eBooks.
Springer Optimization and Its Applications, 191.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b4716346x*spi
Descripción
Sumario: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.
Descripción Física:VIII, 417 páginas, 40 ilustraciones, 33 ilustraciones (color)
Formato:Forma de acceso: World Wide Web.