This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Subspace learning is very important in today's world of information overload. Distinguishing between categories within a subset of a large data repository such as the web and ...
Nandita Tripathi, Michael P. Oakes, Stefan Wermter
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...