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1. |
Record Nr. |
UNISA996475762603316 |
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Autore |
Suzuki Joe |
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Titolo |
Kernel methods for machine learning with math and python : 100 exercises for building logic / / Joe Suzuki |
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Pubbl/distr/stampa |
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Gateway East, Singapore : , : Springer, , [2022] |
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©2022 |
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ISBN |
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9789811904011 |
9789811904004 |
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Descrizione fisica |
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1 online resource (216 pages) |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Artificial intelligence - Data processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Intro -- Preface -- How to Overcome Your Kernel Weakness -- What Makes KMMP Unique? -- Acknowledgments -- Contents -- 1 Positive Definite Kernels -- 1.1 Positive Definiteness of a Matrix -- 1.2 Kernels -- 1.3 Positive Definite Kernels -- 1.4 Probability -- 1.5 Bochner's Theorem -- 1.6 Kernels for Strings, Trees, and Graphs -- Appendix -- Exercises 1 sim 15 -- 2 Hilbert Spaces -- 2.1 Metric Spaces and Their Completeness -- 2.2 Linear Spaces and Inner Product Spaces -- 2.3 Hilbert Spaces -- 2.4 Projection Theorem -- 2.5 Linear Operators -- 2.6 Compact Operators -- Appendix: Proofs of Propositions -- Exercises 16 sim 30 -- 3 Reproducing Kernel Hilbert Space -- 3.1 RKHSs -- 3.2 Sobolev Space -- 3.3 Mercer's Theorem -- Appendix -- Exercises 31 sim 45 -- 4 Kernel Computations -- 4.1 Kernel Ridge Regression -- 4.2 Kernel Principle Component Analysis -- 4.3 Kernel SVM -- 4.4 Spline Curves -- 4.5 Random Fourier Features -- 4.6 Nyström Approximation -- 4.7 Incomplete Cholesky Decomposition -- Appendix -- Exercises 46 sim 64 -- 5 The MMD and HSIC -- 5.1 Random Variables in RKHSs -- 5.2 The MMD and Two-Sample Problem -- 5.3 The HSIC and Independence Test -- 5.4 Characteristic and Universal Kernels -- 5.5 Introduction to Empirical Processes -- Appendix -- Exercises 65 sim83 -- 6 Gaussian Processes and Functional Data Analyses -- 6.1 Regression -- 6.2 Classification -- 6.3 |
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Gaussian Processes with Inducing Variables -- 6.4 Karhunen-Lóeve Expansion -- 6.5 Functional Data Analysis -- Appendix -- Exercises 83sim100 -- Appendix Bibliography. |
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2. |
Record Nr. |
UNINA9910697893703321 |
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Titolo |
Spent fuel transportation package response to the Baltimore Tunnel fire scenario [[electronic resource] ] : final report / / prepared by H.E. Adkins, Jr. ... [and others] |
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Pubbl/distr/stampa |
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Washington, DC : , : Division of Spent Fuel Storage and Transportation, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, , [2007] |
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Edizione |
[Rev. 1.] |
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Descrizione fisica |
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1 electronic text (1 volumes (various pagings)) : HTML, digital, PDF file |
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Altri autori (Persone) |
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Soggetti |
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Spent reactor fuels - Transportation - Safety measures |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed on Nov. 26, 2008). |
"Pacific Northwest National Laboratory." |
"Date published: November 2006." |
"NUREG/CR-6886." |
"PNNL-15313." |
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Nota di bibliografia |
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Includes bibliographical references (page 9.1 - 9.3). |
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