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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