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Titlebook: Harmonic and Applied Analysis; From Radon Transform Filippo De Mari,Ernesto De Vito Book 2021 The Editor(s) (if applicable) and The Author(

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發(fā)表于 2025-3-21 19:06:02 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Harmonic and Applied Analysis
副標(biāo)題From Radon Transform
編輯Filippo De Mari,Ernesto De Vito
視頻videohttp://file.papertrans.cn/425/424311/424311.mp4
概述Explores mathematical connections between harmonic analysis and machine learning, data analysis, and imaging science.Offers a current and accessible entrance into cutting-edge research in the data sci
叢書名稱Applied and Numerical Harmonic Analysis
圖書封面Titlebook: Harmonic and Applied Analysis; From Radon Transform Filippo De Mari,Ernesto De Vito Book 2021 The Editor(s) (if applicable) and The Author(
描述Deep connections exist between harmonic and applied analysis and the diverse yet connected topics of machine learning, data analysis, and imaging science.? This volume explores these rapidly growing areas and features contributions presented at the second and third editions of the Summer Schools on Applied Harmonic Analysis, held at the University of Genova in 2017 and 2019.? Each chapter offers an introduction to essential material and then demonstrates connections to more advanced research, with the aim of providing an accessible entrance for students and researchers.? Topics covered include ill-posed problems; concentration inequalities; regularization and large-scale machine learning; unitarization of the radon transform on symmetric spaces; and proximal gradient methods for machine learning and imaging.??
出版日期Book 2021
關(guān)鍵詞Harmonic Analysis machine learning; Applied harmonic analysis; Concentration inequalities; Ill-posed pr
版次1
doihttps://doi.org/10.1007/978-3-030-86664-8
isbn_softcover978-3-030-86666-2
isbn_ebook978-3-030-86664-8Series ISSN 2296-5009 Series E-ISSN 2296-5017
issn_series 2296-5009
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Andreas Maurers to orchestrate rule execution. They provide a high-level control mechanism and a context for rule execution. Ruleflows offer opportunities for speeding execution through run-time rule selection, and algorithm selection.
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2296-5009 arning; unitarization of the radon transform on symmetric spaces; and proximal gradient methods for machine learning and imaging.??978-3-030-86666-2978-3-030-86664-8Series ISSN 2296-5009 Series E-ISSN 2296-5017
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making The principles of rule engines, and the implications of object-rule systems The basics of the RETE algorithm The different rule engine execution algorithms Key points Rule-based decision making has a long history and some cognitive plausibility. Rules are treated as data processed by an inte
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Francesca Bartolucci,Filippo De Mari,Matteo Montifferent components of a rule project Rule project relationships and their importance in modularizing rule development The Business Object Model (BOM), which is used for rule authoring, and how to build it from the application (or executable) object model Best practices for organizes organizing rules
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Andreas Maurer technical rules, action rules, decision tables, decision trees, and scorecards How to build your custom rule language How to orchestrate rule execution with ruleset parameters and ruleflow How to optimize rule execution by selecting the appropriate rule execution algorithm for a given rule task Key
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