This paper proposes and evaluates several alternate design choices for common prediction metrics employed by neighborhood-based collaborative filtering approach. It first explores ...
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...
Abstract. We analyze special random network models – so-called thickened trees – which are constructed by random trees where the nodes are replaced by local clusters. These obj...
Michael Drmota, Bernhard Gittenberger, Reinhard Ku...
We define a framework called the prismoid of resources where each vertex refines the λ-calculus by using a different choice to make explicit or implicit (meta-level) the defin...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...