Protecting sensitive micro data prior to publishing or passing the data itself on is a crucial aspect: A trade-off between sufficient disclosure control and analyzability needs to be found. This paper presents a starting point to evaluate the effect of k-anonymity microaggregated data in (generalized) linear regression. Taking a rigorous imprecision perspective, microaggregated data are underst...

Composition theorems are tools which reduce reasoning about compound data structures to reasoning about their parts. For example, the truth value of a sentence about the Cartesian product of two structures can be reduced to the truth values of sentences on the components of the product. A seminal example of a compositional theorem is the Feferman-Vaught Theorem [2]. Feferman and Vaught introduc...

In this paper, we study the advanced differential equations r(t) x (t) α–1 x (t) + n i=1 p i (t) x(t + τ i (t)) α–1 x(t + τ i (t)) = 0 and r(t)(y(t) – P(t)y(t – τ)) + n i=1 p i (t)f (y(t + σ)) = 0. By using the generalized Riccati transformation and the Schauder-Tyichonoff theorem, we establish the conditions for the existence of positive solutions of the above equations.

We present a novel ensemble of logistic linear regressors that combines the robustness of online Bayesian learning with the flexibility of ensembles. The ensemble of classifiers are built on top of a Randomly Varying Coefficient model designed for online regression with the fusion of classifiers done at the level of regression before converting it into a class label using a logistic link functi...