In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
In this paper, we propose a hybrid approach for automatic single-organ segmentation in Computed Tomography (CT) data. The approach consists of three stages: first, a probability i...
Ruchaneewan Susomboon, Daniela Stan Raicu, Jacob D...
The problem of privacy-preserving data mining has been studied extensively in recent years because of the increased amount of personal information which is available to corporation...
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...