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1. |
Record Nr. |
UNISA996384923403316 |
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Autore |
Brown John <1610?-1679.> |
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Titolo |
The life of faith in times of trial and affliction [[electronic resource] ] : cleared up and explained from Hebrews X:XXXVIII ... / / by Ioh. Brown . |
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Pubbl/distr/stampa |
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[S.l.], : Printed for the author, 1679-1680 |
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Descrizione fisica |
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2 pts. ([12], 396, [4], 474, [1] p.) |
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Soggetti |
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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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Second pt. ([40], 474, [1] p.) has special t.p.: The swan-song, or, The second part of The life of faith. 1680. |
Errata: p. [1] at end. |
Copy at reel 205:3 (B5030) is parts 1 and 2; copy at reel 17:2 (B5034) is part 2 only. |
Reproduction of original in Union Theological Seminary Library, New York. |
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2. |
Record Nr. |
UNINA9910783421103321 |
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Titolo |
Advances in learning theory [[electronic resource] ] : methods, models, and applications / / edited by Johan Suykens ... [et al.] |
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Pubbl/distr/stampa |
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Amsterdam ; ; Washington, DC, : IOS Press |
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Tokyo, : Ohmsha, c2003 |
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ISBN |
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1-280-50590-7 |
9786610505906 |
1-4175-1139-7 |
600-00-0332-3 |
1-60129-401-8 |
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Descrizione fisica |
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1 online resource (438 p.) |
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Collana |
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NATO science series. Series III, Computer and systems sciences, , 1387-6694 ; ; v. 190 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Computational learning theory |
Machine learning - Mathematical models |
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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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"Proceedings of the NATO Advanced Study Institute on Learning Theory and Practice, 8-19 July 2002, Leuven, Belgium"--T.p. verso. |
"Published in cooperation with NATO Scientific Affairs Division." |
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Nota di bibliografia |
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Includes bibliographical references and indexes. |
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Nota di contenuto |
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Cover; Title page; Preface; Organizing committee; List of chapter contributors; Contents; 1 An Overview of Statistical Learning Theory; 2 Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem; 3 Cucker Smale Learning Theory in Besov Spaces; 4 High-dimensional Approximation by Neural Networks; 5 Functional Learning through Kernels; 6 Leave-one-out Error and Stability of Learning Algorithms with Applications; 7 Regularized Least-Squares Classification; 8 Support Vector Machines: Least Squares Approaches and Extensions |
9 Extension of the ν-SVM Range for Classification10 Kernels Methods for Text Processing; 11 An Optimization Perspective on Kernel Partial Least Squares Regression; 12 Multiclass Learning with Output Codes; 13 Bayesian Regression and Classification; 14 Bayesian Field Theory: from Likelihood Fields to Hyperfields; 15 Bayesian Smoothing and |
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Information Geometry; 16 Nonparametric Prediction; 17 Recent Advances in Statistical Learning Theory; 18 Neural Networks in Measurement Systems (an engineering view); List of participants; Subject Index; Author Index |
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Sommario/riassunto |
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This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics. |
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