We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
The development of the adjoint of the forecast model and of the adjoint of the data assimilation system (adjoint-DAS) make feasible the evaluation of the derivative-based forecast...
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
This study addresses the problem of unsupervised visual learning. It examines existing popular model order selection criteria before proposes two novel criteria for improving visu...