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
- Softcover
- New

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- Title
- Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine . Papers (Lecture Notes in Computer Science)
- Author
- Joaquin Quionero-Candela, Ido Dagan, Bernardo Magnini, Florence d'Alch-Buc
- Publisher
- Springer Berlin Heidelberg 2010-06-02
- Publication year
- 2010
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 3540334270
- ISBN 13
- 9783540334279
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.
"Synopsis" may belong to another edition of this title.
Chiron Media
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