Data warehouses (DWs) can become inconsistent when some dimensional constraints are not satisfied by the dimension instances. In this paper, we present preliminary results about the effects of the violation of partitioning constraints in homogeneous dimension instances over aggregation queries, and in particular over the summarizability property (SUMM) of the DWs. We are interested in finding w...

The purpose of this paper is to discuss empirical risk minimization when the losses are not necessarily bounded and may have a distribution with heavy tails. In such situations usual empirical averages may fail to provide reliable estimates and empirical risk minimization may provide large excess risk. However, some robust mean estimators proposed in the literature may be used to replace empiri...

In this note we study lower bounds on the empirical minimization algorithm. To explain the basic set up of this algorithm, let (Ω, μ) be a probability space and set X to be a random variable taking values in Ω, distributed according to μ. We are interested in the function learning (noiseless) problem, in which one observes n independent random variables X1, . . . , Xn distributed according to μ...

Empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. That is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of VaR. Copula theo...

Building on earlier empirical work we have designed a prototype that supports modeling in groups. The COllaborative Modeling Architecture tool (COMA tool) coordinates UML modeling in groups in the form of a negotiated creation process. We have employed the tool in two case studies.

Steel making is known as a complex manufacturing industrial process. Automation of the process represents a challenge. Empirical mathematical modeling of the process was used to design mill equipment, ensure productivity and service quality. This modeling approach shows many problems associated to complexity and time consumption. Soft computing techniques show significant modeling capabilities ...