Named Entity Recognition is a relatively well-understood NLP task, with many publicly available training resources and software for English. Other languages tend to be underserved...
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
Background: There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large,...