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.
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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.
Imprint | Springer-Verlag |
Country of origin | Germany |
Series | Lecture Notes in Artificial Intelligence, 3944 |
Release date | May 2006 |
Availability | Expected to ship within 10 - 15 working days |
First published | 2006 |
Editors | Joaquin Quinonero-Candela, Ido Dagan, Bernardo Magnini, Florence D'Alche-Buc |
Dimensions | 235 x 155 x 25mm (L x W x T) |
Format | Paperback |
Pages | 462 |
Edition | 2006 ed. |
ISBN-13 | 978-3-540-33427-9 |
Barcode | 9783540334279 |
Categories | |
LSN | 3-540-33427-0 |