In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
Visualising large graphs faces the challenges of both data complexity and visual complexity. This paper presents a framework for visualising large graphs that reduces data complex...
Inner holes, artifacts and blank spots are common in microarray images, but current image analysis methods do not pay them enough attention. We propose a new robust model-based me...
Qunhua Li, Chris Fraley, Roger Eugene Bumgarner, K...