The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
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...
In recent years, there has been an increasing interest in developing geometric algorithms for kinematic computations. The aim of this paper is to present the notion of kinematic c...
Over the years increasingly sophisticated planning algorithms have been developed. These have made for more efficient planners, but unfortunately these planners still suffer from ...
— Most application data units are too large to be carried in a single packet (or cell) and must be segmented for network delivery. To an application, the end-to-end delays and lo...