An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the prosodic lab...
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learne...
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...