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[null,"1.","Record Nr.",null,"UNISA996475762603316"]
[null,null,"Autore",null,"Suzuki Joe"]
[null,null,"Titolo",null,"Kernel methods for machine learning with math and python : 100 exercises for building logic / / Joe Suzuki"]
[null,null,"Pubbl/distr/stampa",null,"Gateway East, Singapore : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"9789811904011"]
[{"$nulls":4},"9789811904004"]
[null,null,"Descrizione fisica",null,"1 online resource (216 pages)"]
[null,null,"Disciplina",null,"515.9"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- How to Overcome Your Kernel Weakness -- What Makes KMMP Unique? -- Acknowledgments -- Contents -- 1 Positive Definite Kernels -- 1.1 Positive Definiteness of a Matrix -- 1.2 Kernels -- 1.3 Positive Definite Kernels -- 1.4 Probability -- 1.5 Bochner's Theorem -- 1.6 Kernels for Strings, Trees, and Graphs -- Appendix -- Exercises 1 sim 15 -- 2 Hilbert Spaces -- 2.1 Metric Spaces and Their Completeness -- 2.2 Linear Spaces and Inner Product Spaces -- 2.3 Hilbert Spaces -- 2.4 Projection Theorem -- 2.5 Linear Operators -- 2.6 Compact Operators -- Appendix: Proofs of Propositions -- Exercises 16 sim 30 -- 3 Reproducing Kernel Hilbert Space -- 3.1 RKHSs -- 3.2 Sobolev Space -- 3.3 Mercer's Theorem -- Appendix -- Exercises 31 sim 45 -- 4 Kernel Computations -- 4.1 Kernel Ridge Regression -- 4.2 Kernel Principle Component Analysis -- 4.3 Kernel SVM -- 4.4 Spline Curves -- 4.5 Random Fourier Features -- 4.6 Nyström Approximation -- 4.7 Incomplete Cholesky Decomposition -- Appendix -- Exercises 46 sim 64 -- 5 The MMD and HSIC -- 5.1 Random Variables in RKHSs -- 5.2 The MMD and Two-Sample Problem -- 5.3 The HSIC and Independence Test -- 5.4 Characteristic and Universal Kernels -- 5.5 Introduction to Empirical Processes -- Appendix -- Exercises 65 sim83 -- 6 Gaussian Processes and Functional Data Analyses -- 6.1 Regression -- 6.2 Classification -- 6.3 Gaussian Processes with Inducing Variables -- 6.4 Karhunen-Lóeve Expansion -- 6.5 Functional Data Analysis -- Appendix -- Exercises "]
[{"$nulls":4},"83sim100 -- Appendix  Bibliography."]
[null,"2.","Record Nr.",null,"UNINA9910808649403321"]
[null,null,"Titolo",null,"Language acquisition : problems and perspectives / / edited by Diana Laiveniece"]
[null,null,"Pubbl/distr/stampa",null,"Newcastle upon Tyne, England : , : Cambridge Scholars Publishing, , 2016"]
[{"$nulls":4},"2016"]
[null,null,"ISBN",null,"1-4438-9006-5"]
[null,null,"Descrizione fisica",null,"1 online resource (292 p.)"]
[null,null,"Disciplina",null,"418.0071"]
[null,null,"Soggetti",null,"Language and languages - Study and teaching - Baltic States"]
[{"$nulls":4},"Language acquisition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references at the end of each chapters."]
[null,null,null,"Sommario/riassunto","This volume brings together a selection of articles about research conducted on language acquisition in the Baltic States, namely in Latvia and Lithuania, a field which has witnessed massive growth in recent years. The book begins with an introduction which specifies the problems investigated by the contributions in order to acquaint the reader with current issues and research in linguodidactics and applied linguistics. The volume will particularly appeal to scholars of language acquisition, as well as anyone interested in research and practical activities concerning language education in the"]