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...
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
A rogue insider, in a wireless network, is an authenticated member that exploits possession of a valid identity in order to launch an attack. A typical example is the transmission...
This paper introduces a novel method for real-time estimation of slowly varying parameters in nonlinear dynamical systems. The core concept is built upon the principles of symboli...