In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
—In the future smart city, new information and communication technologies will enable a better management of the available resources. The future smart grid infrastructure is emer...
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
—A computational framework is presented for surface based morphometry to localize shape changes between groups of 3D objects. It employs the spherical harmonic (SPHARM) method fo...
Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huan...