For the natural notion of splitting classes into two disjoint subclasses via a recursive classifier working on texts, the question is addressed how these splittings can look in th...
We give an algorithm that learns any monotone Boolean function f : {-1, 1}n {-1, 1} to any constant accuracy, under the uniform distribution, in time polynomial in n and in the de...
The paper presents a flexible framework for the online evaluation of collaborative project-oriented e-learning platforms. The framework was developed for the evaluation of the COOP...
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...