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Statistical Relational Artificial Intelligence: Logic, Probability, and Computation (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Book 7 of 14: Synthesis Lectures on Artificial Intelligence and Machine LearningSeller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Very Good.
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paperback. Condition: Good. Crease/tear to cover.
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paperback. Condition: Very Good. Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.
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An Introduction to Lifted Probabilistic Inference (Neural Information Processing series)
Book 2 of 2: Neural Information ProcessingSeller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
Paperback. Condition: Fine.
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Condition: As New. Unread book in perfect condition.
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Boosted Statistical Relational Learners (Paperback)
Book 172 of 322: SpringerBriefs in Computer ScienceLanguage: English
Published by Springer International Publishing AG, Cham, 2015
ISBN 10: 3319136437 ISBN 13: 9783319136431
Paperback. Condition: new. Paperback. This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications.The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems.Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource. This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Boosted Statistical Relational Learners: From Benchmarks to Data-Driven Medicine (SpringerBriefs in Computer Science)
Book 172 of 322: SpringerBriefs in Computer ScienceSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 48.98
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Statistical Relational Artificial Intelligence: Logic, Probability, and Computation (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Book 7 of 14: Synthesis Lectures on Artificial Intelligence and Machine LearningSeller: 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 English.
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Boosted Statistical Relational Learners : From Benchmarks to Data-Driven Medicine
Book 172 of 322: SpringerBriefs in Computer ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Boosted Statistical Relational Learners : From Benchmarks to Data-Driven Medicine
Book 172 of 322: SpringerBriefs in Computer ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Paperback. Condition: Brand New. 2014 edition. 74 pages. 9.00x6.00x0.25 inches. In Stock.
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Condition: As New. Unread book in perfect condition.
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An Introduction to Lifted Probabilistic Inference (Neural Information Processing series)
Book 2 of 2: Neural Information ProcessingSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 70.47
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In English.
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Introduction to Lifted Probabilistic Inference
Book 2 of 2: Neural Information ProcessingSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Introduction to Lifted Probabilistic Inference
Book 2 of 2: Neural Information ProcessingSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Introduction to Lifted Probabilistic Inference (Neural Information Processing series)
Book 2 of 2: Neural Information ProcessingSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2021. paperback. . . . . .
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Introduction to Lifted Probabilistic Inference
Book 2 of 2: Neural Information ProcessingSeller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications.The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.
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Taschenbuch. Condition: Neu. Boosted Statistical Relational Learners | From Benchmarks to Data-Driven Medicine | Sriraam Natarajan (u. a.) | Taschenbuch | viii | Englisch | 2015 | Springer | EAN 9783319136431 | 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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Paperback. Condition: Brand New. 429 pages. 9.25x7.25x1.25 inches. In Stock.
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Condition: New. 2021. paperback. . . . . . Books ship from the US and Ireland.
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Intelligent Assistants - A Decision-Theoretic Model | Effective Decision-Theoretic Assistance Through Relational Hierarchical Models
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639145801 ISBN 13: 9783639145809
Taschenbuch. Condition: Neu. Intelligent Assistants - A Decision-Theoretic Model | Effective Decision-Theoretic Assistance Through Relational Hierarchical Models | Sriraam Natarajan | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639145809 | 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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Boosted Statistical Relational Learners (Paperback)
Book 172 of 322: SpringerBriefs in Computer ScienceLanguage: English
Published by Springer International Publishing AG, Cham, 2015
ISBN 10: 3319136437 ISBN 13: 9783319136431
Paperback. Condition: new. Paperback. This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications.The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems.Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource. This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Paperback. Condition: New.
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Condition: new. Questo è un articolo print on demand.
