This paper presents a model reduction algorithm motivated by a connection between frequency domain projection methods and approximation of truncated balanced realizations. The met...
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
This paper concerns problem of selection of optimal subset of irredundant unconditional diagnostic tests by means of evolutionary approach. The method of correction of features’...
Abstract. While injecting fault during training has long been demonstrated as an effective method to improve fault tolerance of a neural network, not much theoretical work has been...
We propose an environment for musical constraint solving, in the visual programming language OpenMusic. We describe an implementation of a local search algorithm, called adaptive s...