Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
We present a probabilistic model of diachronic phonology in which individual word forms undergo stochastic edits along the branches of a phylogenetic tree. Our approach allows us ...
Nonnegative matrix tri-factorization (NMTF) is a 3-factor decomposition of a nonnegative data matrix, X USV , where factor matrices, U, S, and V , are restricted to be nonnegativ...
Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring u...
Abstract. This paper considers the probabilistic may/must testing theory for processes having external, internal, and probabilistic choices. We observe that the underlying testing ...