Abstract--In this paper, we introduce a novel approach to timeseries prediction realized both at the linguistic and numerical level. It exploits fuzzy cognitive maps (FCMs) along w...
—Grid applications need to move large amounts of data between distributed resources within deterministic time frames. In most cases it is possible to specify the volume and the d...
Kashif Munir, Pascale Vicat-Blanc Primet, Michael ...
— In this paper we present a structure theory for generalized linear dynamic factor models (GDFM’s). Emphasis is laid on the so-called zeroless case. GDFM’s provide a way of ...
Computing the degree of semantic relatedness of words is a key functionality of many language applications such as search, clustering, and disambiguation. Previous approaches to c...
Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovi...
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...