9781852333737 - learning and generalisation: with applications to neural networks di vidyasagar, mathukumalli (12 risultati)

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Hardcover. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 512 | Sprache: Englisch | Produktart: Bücher | Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: ¿ How does a machine learn a concept on the basis of examples? ¿ How can a neural network, after training, correctly predic…t the outcome of a previously unseen input? ¿ How much training is required to achieve a given level of accuracy in the prediction? ¿ How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite time? The second edition covers new areas including: ¿ support vector machines; ¿ fat-shattering dimensions and applications to neural network learning; ¿ learning with dependent samples generated by a beta-mixing process; ¿ connections between system identification and learning theory; ¿ probabilistic solution of 'intractable problems' in robust control and matrix theory using randomized algorithms. It also contains solutions to some of the open problems posed in the first edition, while adding new open problems.

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Hardcover. Condizione: gut. 2002. Learning and Generalisation In deutscher Sprache. pages.

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Condizione: New. pp. 512 2nd Edition.

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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: - How does a machine learn a concept on the basis of examples - How can a neural network, after training, correctly predict the outcome of a pre…viously unseen input - How much training is required to achieve a given level of accuracy in the prediction - How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite time The second edition covers new areas including:- support vector machines;- fat-shattering dimensions and applications to neural network learning;- learning with dependent samples generated by a beta-mixing process;- connections between system identification and learning theory;- probabilistic solution of 'intractable problems' in robust control and matrix theory using randomized algorithms.It also contains solutions to some of the open problems posed in the first edition, while adding new open problems.

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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive this book covers all aspects of learning theory and its applications. Other books have a narrower focus  It contains applications not only to neural networks but also to control systems The auth…or has .

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -How does a machine learn a new concept on the basis of examples This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to…learning of neural networks. 512 pp. Englisch.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type:¿ How does a machine learn a concept on the basis of examples ¿ How can a neural network, after training, correctly predict the outco…me of a previously unseen input ¿ How much training is required to achieve a given level of accuracy in the prediction ¿ How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite time The second edition covers new areas including:¿ support vector machines;¿ fat-shattering dimensions and applications to neural network learning;¿ learning with dependent samples generated by a beta-mixing process;¿ connections between system identification and learning theory;¿ probabilistic solution of 'intractable problems' in robust control and matrix theory using randomized algorithms.It also contains solutions to some of the open problems posed in the first edition, while adding new open problems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 512 pp. Englisch.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 512 Illus.

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 512.