Abstract—We introduce and validate Spatiotemporal Relational Random Forests, which are random forests created with spatiotemporal relational probability trees. We build on the do...
Timothy A. Supinie, Amy McGovern, John Williams, J...
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Knowledge discovery, that is, to analyze a given massive data set and derive or discover some knowledge from it, has been becoming a quite important subject in several fields incl...
We develop an infrastructure for managing, indexing and serving multimedia content in digital libraries. This infrastructure follows the model of the web, and thereby is distribut...
Arjen P. de Vries, Brian S. Eberman, David E. Kova...
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...