In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Background: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although...
Wei Yu, Melinda Clyne, Siobhan M. Dolan, Ajay Yesu...
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...