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Titlebook: High-Dimensional Optimization and Probability; With a View Towards Ashkan Nikeghbali,Panos M. Pardalos,Michael Th. Ra Book 2022 The Editor

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发表于 2025-3-21 16:22:22 | 显示全部楼层 |阅读模式
书目名称High-Dimensional Optimization and Probability
副标题With a View Towards
编辑Ashkan Nikeghbali,Panos M. Pardalos,Michael Th. Ra
视频videohttp://file.papertrans.cn/427/426570/426570.mp4
概述Provides new directions for further research.Features highly interdisciplinary topics.Serves as a reference to a large community of researchers
丛书名称Springer Optimization and Its Applications
图书封面Titlebook: High-Dimensional Optimization and Probability; With a View Towards  Ashkan Nikeghbali,Panos M. Pardalos,Michael Th. Ra Book 2022 The Editor
描述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 gr
出版日期Book 2022
关键词high-dimensional optimization; deterministic global optimization; probability theory; data science; mach
版次1
doihttps://doi.org/10.1007/978-3-031-00832-0
isbn_softcover978-3-031-00834-4
isbn_ebook978-3-031-00832-0Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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