Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop

Quinonero-candela, Joaquin (Editor)/ Dagan, Ido (Editor)/ Magnini, Bernardo (Editor)/ D'alche-buc, Florence (Editor)

ISBN 10: 3540334270 / ISBN 13: 9783540334279

Published by Springer-Verlag New York Inc, 2006

About this Item

1st edition. 462 pages. 9.25x6.25x0.75 inches. In Stock.

Seller Inventory # x-3540334270

Bibliographic Details

• Title: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop
• Publisher: Springer-Verlag New York Inc
• Publication Date: 2006
• Language: English
• ISBN 10: 3540334270
• ISBN 13: 9783540334279
• Binding: Paperback
• Condition: Brand New
• Weight: 1.77 kilograms

About this title

Synopsis

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.