Publicado por Springer Berlin Heidelberg, 2003
ISBN 10: 3540005293 ISBN 13: 9783540005292
Idioma: Inglés
Librería: Buchpark, Trebbin, Alemania
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Librería: Zubal-Books, Since 1961, Cleveland, OH, Estados Unidos de America
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Añadir al carritoCondición: Fine. 276 pp., paperback, this is the 2018 later printing, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.
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Añadir al carritoSoftcover. Condición: Gut. Gebraucht - Gut Zustand: Gut, IX, 259 p. Also available online. About this book: This book presents revised reviewed versions of lectures given during the Machine Learning Summer School held in Canberra, Australia, in February 2002. The lectures address the following key topics in algorithmic learning: statistical learning theory, kernel methods, boosting, reinforcement learning, theory learning, association rule learning, and learning linear classifier systems. Thus, the book is well balanced between classical topics and new approaches in machine learning. Advanced students and lecturers will find this book a coherent in-depth overview of this exciting area, while researchers will use this book as a valuable source of reference. Written for researchers and professionals.
Publicado por Springer, 2003, 2003
Librería: Longhouse, Publishers & Booksellers, Brattleboro, VT, Estados Unidos de America
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Añadir al carritoVery fine and bright glossy stiff wraps with strong square spine and crisp bright text throughout. As new. Profusely illustrated.
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Springer Berlin Heidelberg, 2003
ISBN 10: 3540005293 ISBN 13: 9783540005292
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 48,10
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11-22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.
Publicado por Springer Berlin Heidelberg, 2003
ISBN 10: 3540005293 ISBN 13: 9783540005292
Idioma: Inglés
Librería: moluna, Greven, Alemania
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Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2003, 2003
ISBN 10: 3540005293 ISBN 13: 9783540005292
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11¿22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Springer Berlin Heidelberg Jan 2003, 2003
ISBN 10: 3540005293 ISBN 13: 9783540005292
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 48,10
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11-22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop. 268 pp. Englisch.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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Añadir al carritoCondición: New. Print on Demand pp. 276 Illus.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 276.