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An Architecture for Combinator Graph Reduction
Language: English
Published by Elsevier Science & Technology, 1990
ISBN 10: 0124192408 ISBN 13: 9780124192409
Condition: 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.
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Paperback. Condition: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
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Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Text block clean and unmarked. Tight binding.
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction (Paperback or Softback)
Language: English
Published by Dissertation.com 10/20/2011, 2011
ISBN 10: 1612337570 ISBN 13: 9781612337579
Paperback or Softback. Condition: New. Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction. Book.
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Condition: As New. Unread book in perfect condition.
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 46.31
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 43.04
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction
Language: English
Published by Dissertation.Com 2011-10-20, 2011
ISBN 10: 1612337570 ISBN 13: 9781612337579
US$ 38.69
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 42.09
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US$ 46.08
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Add to basketPaperback. Condition: Brand New. 172 pages. 9.25x6.00x0.39 inches. In Stock.
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Head-Order Techniques and Other Pragmatics of Lambda Calculus Graph Reduction
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 46.72
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Add to basketCondition: As New. Unread book in perfect condition.
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Condition: New. pp. 168 1st ed. 2024 edition NO-PA16APR2015-KAP.
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Graph Reduction: Proceedings of a Workshop Santa Fe, New Mexico, USA, September 29 - October 1, 1986 (Lecture Notes in Computer Science, 279)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 69.23
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US$ 65.85
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. pp. xvi + 450.
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Condition: New. pp. xvi + 450 Illus.
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Condition: New. pp. xvi + 450.
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Dynamic Graph Learning for Dimension Reduction and Data Clustering
Book 7 of 13: Synthesis Lectures on Computer ScienceLanguage: English
Published by Springer Nature Switzerland, 2024
ISBN 10: 3031423151 ISBN 13: 9783031423154
Taschenbuch. Condition: 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.
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Dynamic Graph Learning for Dimension Reduction and Data Clustering
Book 7 of 13: Synthesis Lectures on Computer ScienceLanguage: English
Published by Springer Nature Switzerland, Springer International Publishing, 2023
ISBN 10: 3031423127 ISBN 13: 9783031423123
Buch. Condition: 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.
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Taschenbuch. Condition: 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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Taschenbuch. Condition: 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.
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Taschenbuch. Condition: 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.
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Condition: 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.
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Physical Model Reduction | A Bond Graph Approach for Engineering Systems
Language: English
Published by LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838349857 ISBN 13: 9783838349855
Taschenbuch. Condition: 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.
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Condition: 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.
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US$ 142.77
US$ 33.32 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Very Good. Dust Jacket may NOT BE INCLUDED.CDs may be missing. SHIPS FROM MULTIPLE LOCATIONS. book.
