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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Springer Berlin Heidelberg, 2007
ISBN 10: 3540749578 ISBN 13: 9783540749578
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was rstheldin1997inTrondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in machine learning and data mining. In 2007, the seventh collocated ECML/PKDD took place during September 17-21 on the centralcampus of WarsawUniversityand in the nearby Staszic Palace of the Polish Academy of Sciences. The conference for the third time used a hierarchical reviewing process. We nominated 30 Area Chairs, each of them responsible for one sub- eld or several closely related research topics. Suitable areas were selected on the basis of the submission statistics for ECML/PKDD 2006 and for last year's International Conference on Machine Learning (ICML 2006) to ensure a proper load balance amongtheAreaChairs.AjointProgramCommittee(PC)wasnominatedforthe two conferences, consisting of some 300 renowned researchers, mostly proposed by the Area Chairs. This joint PC, the largest of the series to date, allowed us to exploit synergies and deal competently with topic overlaps between ECML and PKDD. ECML/PKDD 2007 received 592 abstract submissions. As in previous years, toassistthereviewersandtheAreaChairsintheir nalrecommendationauthors had the opportunity to communicate their feedback after the reviewing phase.
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg Sep 2007, 2007
ISBN 10: 3540749578 ISBN 13: 9783540749578
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was rstheldin1997inTrondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in machine learning and data mining. In 2007, the seventh collocated ECML/PKDD took place during September 17¿21 on the centralcampus of WarsawUniversityand in the nearby Staszic Palace of the Polish Academy of Sciences. The conference for the third time used a hierarchical reviewing process. We nominated 30 Area Chairs, each of them responsible for one sub- eld or several closely related research topics. Suitable areas were selected on the basis of the submission statistics for ECML/PKDD 2006 and for last year¿s International Conference on Machine Learning (ICML 2006) to ensure a proper load balance amongtheAreaChairs.AjointProgramCommittee(PC)wasnominatedforthe two conferences, consisting of some 300 renowned researchers, mostly proposed by the Area Chairs. This joint PC, the largest of the series to date, allowed us to exploit synergies and deal competently with topic overlaps between ECML and PKDD. ECML/PKDD 2007 received 592 abstract submissions. As in previous years, toassistthereviewersandtheAreaChairsintheir nalrecommendationauthors had the opportunity to communicate their feedback after the reviewing phase.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 836 pp. Englisch.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 103,32
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Publicado por Springer-Verlag New York Inc, 2007
ISBN 10: 3540749578 ISBN 13: 9783540749578
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 159,54
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Añadir al carritoPaperback. Condición: Brand New. 1st edition. 809 pages. 9.00x6.00x1.00 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
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Publicado por Springer Berlin Heidelberg, 2007
ISBN 10: 3540749578 ISBN 13: 9783540749578
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the 18th European Conference on Machine Learning, ECML 2007, held in Warsaw, Poland, September 2007, jointly with PKDD 2007. The 41 revised full papers and 37 revised short papers presented together with .
Publicado por Springer Berlin Heidelberg Sep 2007, 2007
ISBN 10: 3540749578 ISBN 13: 9783540749578
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 18th European Conference on Machine Learning, ECML 2007, held in Warsaw, Poland, September 2007, jointly with PKDD 2007. The 41 revised full papers and 37 revised short papers presented together with abstracts of four invited talks were carefully reviewed and selected from 592 abstracts submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning. 836 pp. Englisch.