The combination of classifiers leads to substantial reduction of misclassification error in a wide range of applications and benchmark problems. We suggest to use the out-of-bag sample for combining different classifiers. In our setup, a Linear Discriminant Analysis is performed using the...

We prove that, for low-order ( ≤ 4) stable polynomial segments or interval polynomials, there always exists a fixed polynomial such that their ratio is SPR-invariant, thereby providing a rigorous proof of Anderson's claim on SPR synthesis for the fourth-order stable interval polynomials....

Empirical lifetime distributions sometimes have a bathtub-shaped failure rate. This paper deals with some models having a bathtub-shaped failure rate. The root-mean-square criterion is proposed for selection of the best model. Besides two criteria of optimum burn-in time are proposed. The...

We present a model that allows for a relatively simple analytical valuation of a full requirements contract in terms of power forward prices and load in the case when power forward prices follow a geometric Brownian motion and load follows a mean-reverting process. This model represents a...

We developed a method for workforce scheduling that models both the structure of the set of permissible shifts, and the stochastic and time-varying demand process. A prototype implementation uses a genetic algorithm to search for good schedules, and evaluates the service level resulting from a...

We present a model that allows for a relatively simple analytical valuation of a full requirements contract in terms of power forward prices and load in the case when power forward prices follow a geometric Brownian motion and load follows a geometric mean-reverting process. This model...

We present a model that allows for a relatively simple analytical valuation of a full requirements contract in terms of power spot prices and load in the case when both power spot prices and load follow geometric mean-reverting processes. This model represents a practically important special...

We propose an improved method for generalized constrained canonical correlation analysis (GCCANO). In GCCANO, data matrices are first decomposed into several submatrices according to some external information on rows and columns of the data matrices. Decomposed matrices are then subjected to...