Abstract. We describe methods for high-performance and high-quality rendering of point models, including advanced shading, anti-aliasing, and transparency. we keep the rendering qu...
We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...
In this paper we demonstrate the generalization property of spiking neurons trained with ReSuMe method. We show in a set of experiments that the learning neuron can approximate the...
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
Abstract—This work proposes a novel approach - personalized forecasting - to take into account the sequential effect in predicting student performance (PSP). Instead of using all...