Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
Abstract. Bias variance decomposition for classifiers is a useful tool in understanding classifier behavior. Unfortunately, the literature does not provide consistent guidelines on...
We describe two corpora of question and answer pairs collected for complex, open-domain Question Answering (QA) to enable answer classification and re-ranking experiments. We deli...
We describe work on automatically assigning labels to books using user-defined tags as the label set. Using supervised learning and exploring both binary and multiclass classifica...