Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
Understanding what are the characteristics of proteinprotein interfaces is at the core of numerous applications. This paper introduces a method in which the proteins are described...
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
In this paper we address the problem of visual surveillance, which we define as the problem of optimally extracting information from the visual scene with a fixating, foveated ima...
Raghu G. Raj, Wilson S. Geisler, Robert A. Frazor,...
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize the...