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Machine Learning Challenges Evaluating (6 results)
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Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments.
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... (Lecture Notes in Computer Science, 3944)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 49.30
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine . Papers (Lecture Notes in Computer Science)
Language: English
Published by Springer Berlin Heidelberg 2010-06-02, 2010
ISBN 10: 3540334270 ISBN 13: 9783540334279
Paperback. Condition: New.
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop
Language: English
Published by Springer-Verlag New York Inc, 2006
ISBN 10: 3540334270 ISBN 13: 9783540334279
Paperback. Condition: Brand New. 1st edition. 462 pages. 9.25x6.25x0.75 inches. In Stock.
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Machine Learning Challenges : Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
Language: English
Published by Springer Berlin Heidelberg, 2006
ISBN 10: 3540334270 ISBN 13: 9783540334279
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
