For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
While conditional random fields (CRFs) have been applied successfully in a variety of domains, their training remains a challenging task. In this paper, we introduce a novel trai...
Lin Liao, Tanzeem Choudhury, Dieter Fox, Henry A. ...
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Abstract—The problem of hypothesis testing against independence for a Gauss–Markov random field (GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the...
Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine l...