We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as ...
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
: This paper describes the successful parallel implementation of genetic programming on a network of processing nodes using the transputer architecture. With this approach, researc...
In this paper, a new method is proposed in order to evaluate the stochastic solution of linear random differential equation. The method is based on the combination of the probabili...
Linear Discriminant Analysis (LDA) is widely known feature extraction technique that aims at creating a feature set of enhanced discriminatory power. It was addressed by many resea...
Krzysztof Kucharski, Wladyslaw Skarbek, Miroslaw B...