In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
- Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised lea...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...