We recently proposed a new incremental procedure for supervised learning with noisy data. Each step consists in adding to the current network a new unit (or small 2-or 3-neuron networks) which is trained to learn the error of the network. The incremental step is repeated until the error of the current network can be considered as a noise. The stopping criterion is very simple and can be directl...

The stopping condition is a common problem for non-regularized deconvolution methods. We introduce an automatic procedure for estimating the ideal stopping point based on a new measure of independence, checking an orthogonality criterion of the estimated signal and its gradient at a given iteration. We provide an effective lower bound estimate than the conventional ad-hoc methods, proving its s...

The estimation of image quality and noise perception still remains an important issue in various processing applications. It has also become a hot topic the field photo-realistic computer graphics where is inherent calculation process. Unlike natural-scene images, however, reference not available for computer-generated images. Thus, classic methods to assess quantity stopping criterion during r...

When an iterative method is applied to solve the linear equation system in interior point methods (IPMs), attention usually placed on accelerating their convergence by designing appropriate preconditioners, but solver as a black box with standard termination criterion which asks for sufficient reduction of residual system. Such approach often leads unnecessary 'oversolving' equations. In this p...