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Softcover. Condition: Très bon. Ancien livre de bibliothèque. Edition 1989. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1989. Ammareal gives back up to 15% of this item's net price to charity organizations.
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Uberzeugungssysteme der Kunstlichen Intelligenz. Validierung vor dem Hintergrund linguistischer Theorien über implizite Ausserungen. (ISBN: 3484319054)
Seller: Zubal-Books, Since 1961, Cleveland, OH, U.S.A.
Seller rating 5 out of 5 stars
Condition: Very Good. 269 pp., Paperback, very good. - 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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Überzeugungssysteme der künstlichen Intelligenz : Validierung vor d. Hintergrund linguist. Theorien über implizierte Äusserungen. Sprache und Information ; Bd. 5
Seller: books4less (Versandantiquariat Petra Gros GmbH & Co. KG), Welling, Germany
Seller rating 5 out of 5 stars
Broschiert. Condition: Gut. 269 Seiten; Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). Sprache: Deutsch Gewicht in Gramm: 535.
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Condition: Gut. Auflage: 1989. 340 Seiten Exemplar aus einer wissenchaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 469 1,5 x 2,0 x 23,5 cm, Taschenbuch.
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Local Pattern Detection : International Seminar: Dagstuhl Castle, Germany, April 2004, Revised Selected Papers
Language: English
Published by Springer Berlin / Heidelberg, 2005
ISBN 10: 3540265430 ISBN 13: 9783540265436
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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Computational Sustainability.
Book 163 of 538: Studies in Computational IntelligenceSeller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 4 out of 5 stars
vi, 276 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.
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GWAI-87 11th German Workshop on Artificial Intelligence: Geseke, September 28-October 2, 1987 Proceedings (Subreihe Künstliche Intelligenz)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.43
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Knowledge Representation and Organization in Machine Learning (Lecture Notes in Computer Science, 347)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.43
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Local Pattern Detection: International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers (Lecture Notes in Computer Science, 3539)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.43
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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PF. Condition: New.
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Local Pattern Detection : International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 248.
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Paperback. Condition: new. Paperback. Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 2 covers machine learning for knowledge discovery in particle and astroparticle physics. Their instruments, e.g., particle detectors or telescopes, gather petabytes of data. Here, machine learning is necessary not only to process the vast amounts of data and to detect the relevant examples efficiently, but also as part of the knowledge discovery process itself. The physical knowledge is encoded in simulations that are used to train the machine learning models. At the same time, the interpretation of the learned models serves to expand the physical knowledge. This results in a cycle of theory enhancement supported by machine learning. Volume 2 covers knowledge discovery in particle and astroparticle physics. Instruments gather petabytes of data and machine learning is used to process the vast amounts of data and to detect relevant examples efficiently. The physical knowledge is e Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Machine Learning under Resource Constraints - Discovery in Physics
Book 172 of 256: De Gruyter STEMSeller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 2 covers machine learning for knowledge discovery in particle and astroparticle physics. Their instruments, e.g., particle detectors or telescopes, gather petabytes of data. Here, machine learning is necessary not only to process the vast amounts of data and to detect the relevant examples efficiently, but also as part of the knowledge discovery process itself. The physical knowledge is encoded in simulations that are used to train the machine learning models. At the same time, the interpretation of the learned models serves to expand the physical knowledge. This results in a cycle of theory enhancement supported by machine learning.
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Condition: New. pp. 420.
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Gwai-87 11th German Workshop on Artificial Intelligence: Geseke, September 28-october 2, 1987 Proceedings
Language: English
Published by Springer-Verlag New York Inc, 1987
ISBN 10: 3540183884 ISBN 13: 9783540183884
Paperback. Condition: Brand New. bilingual edition. 420 pages. German language. 9.60x6.69x0.86 inches. In Stock.
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Überzeugungssysteme der künstlichen Intelligenz. Spradche und Information Band 5
Published by Max Niemeyer Tübingen, 1982
Seller: Abrahamschacht-Antiquariat Schmidt, Freiberg, Germany
Seller rating 4 out of 5 stars
Gr.8° Broschiert. ohne Schutzumschlag, geringe Gebrauchsspuren an Einband und Block, Block sauber und fest ohne Einträge Eintrag im Vorsatz 270 Deutsch 450g.
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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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GWAI-87 11th German Workshop on Artificial Intelligence
Language: English
Published by Springer Berlin Heidelberg, 1987
ISBN 10: 3540183884 ISBN 13: 9783540183884
Condition: New.
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Machine Learning under Resource Constraints - Discovery in Physics
Book 172 of 256: De Gruyter STEMSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Machine Learning under Resource Constraints - Applications
Book 171 of 256: De Gruyter STEMSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Machine Learning under Resource Constraints - Fundamentals
Book 176 of 256: De Gruyter STEMSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Kartoneinband 24x17. Condition: Gut. 319 Seiten altersentsprechend gebrauchtes gutes Exemplar, Einband leicht berieben, Inhalt ist gut bis sehr gut erhalten, mit Widmung von der Autorin als Geschenk ha1006824 Sprache: Englisch Gewicht in Gramm: 650.
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Condition: As New. Unread book in perfect condition.
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Local Pattern Detection
Language: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2005, 2005
ISBN 10: 3540265430 ISBN 13: 9783540265436
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti c and commercial information. The need to analyze these masses of data has led to the evolution of the new eld knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the eld o ers the opportunity to combine the expertise of di erent elds intoacommonobjective.Moreover,withineach elddiversemethodshave been developed and justi ed with respect to di erent quality criteria. We have toinvestigatehowthesemethods cancontributeto solvingthe problemofKDD. Traditionally, KDD was seeking to nd global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to nd only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new eld of local patterns.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 248 pp. Englisch.
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Condition: New.
