Lingua: Inglese
Editore: Elsevier Science & Technology, 1990
ISBN 10: 0124192408 ISBN 13: 9780124192409
Da: Better World Books: West, Reno, NV, U.S.A.
Condizione: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Paperback. Condizione: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
Paperback. Condizione: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Text block clean and unmarked. Tight binding.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 32,72
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Dissertation.com 10/20/2011, 2011
ISBN 10: 1612337570 ISBN 13: 9781612337579
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction. Book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 37,77
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 37,00
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Lingua: Inglese
Editore: Dissertation.Com 2011-10-20, 2011
ISBN 10: 1612337570 ISBN 13: 9781612337579
Da: Chiron Media, Wallingford, Regno Unito
EUR 33,27
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 172 pages. 9.25x6.00x0.39 inches. In Stock.
Condizione: New.
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Da: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloCondizione: New.
Condizione: New. pp. 168 1st ed. 2024 edition NO-PA16APR2015-KAP.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 59,52
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Da: Chiron Media, Wallingford, Regno Unito
EUR 56,62
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Aggiungi al carrelloPF. Condizione: New.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: New. pp. xvi + 450.
EUR 87,07
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Aggiungi al carrelloCondizione: New. pp. xvi + 450 Illus.
EUR 86,22
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Aggiungi al carrelloCondizione: New. pp. xvi + 450.
Lingua: Inglese
Editore: Springer Nature Switzerland, 2024
ISBN 10: 3031423151 ISBN 13: 9783031423154
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 42,79
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.
Lingua: Inglese
Editore: Springer Nature Switzerland, Springer International Publishing, 2023
ISBN 10: 3031423127 ISBN 13: 9783031423123
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 42,79
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.
Da: preigu, Osnabrück, Germania
EUR 41,35
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Dynamic Graph Learning for Dimension Reduction and Data Clustering | Lei Zhu (u. a.) | Taschenbuch | Synthesis Lectures on Computer Science | xxi | Englisch | 2024 | Springer | EAN 9783031423154 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Aggiungi al carrelloPaperback. Condizione: New.
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume describes recent research in graph reduction and related areas of functional and logic programming, as reported at a workshop in 1986. The papers are based on the presentations, and because the final versions were prepared after the workshop, they reflect some of the discussions as well. Some benefits of graph reduction can be found in these papers: - A mathematically elegant denotational semantics - Lazy evaluation, which avoids recomputation and makes programming with infinite data structures (such as streams) possible - A natural tasking model for fine-to-medium grain parallelism. The major topics covered are computational models for graph reduction, implementation of graph reduction on conventional architectures, specialized graph reduction architectures, resource control issues such as control of reduction order and garbage collection, performance modelling and simulation, treatment of arrays, and the relationship of graph reduction to logic programming.
Da: preigu, Osnabrück, Germania
EUR 50,25
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Graph Reduction | Proceedings of a Workshop Santa Fe, New Mexico, USA, September 29 - October 1, 1986 | Joseph H. Fasel (u. a.) | Taschenbuch | xvi | Englisch | 1987 | Springer | EAN 9783540184201 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Buchpark, Trebbin, Germania
EUR 22,44
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838349857 ISBN 13: 9783838349855
Da: preigu, Osnabrück, Germania
EUR 57,95
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Physical Model Reduction | A Bond Graph Approach for Engineering Systems | Ali Yurdun Orbak | Taschenbuch | 184 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838349855 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Da: Buchpark, Trebbin, Germania
EUR 32,17
Quantità: 7 disponibili
Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.