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...
Abstract. User behaviors on a system vary not only among individuals but also within the same user when he/she gains experience on the system. We empirically investigated how indiv...
Kazunori Komatani, Tatsuya Kawahara, Hiroshi G. Ok...
Abstract— A novel nonparametric paradigm to model identification has been recently proposed where, in place of postulating finite-dimensional models of the system transfer func...
Gianluigi Pillonetto, Alessandro Chiuso, Giuseppe ...
A novel no-reference blockiness metric that can automatically and perceptually quantify blocking artifacts of DCT coding is presented. The proposed metric is built upon the specif...
We describe a recommender system based on Dynamically Structured Holographic Memory (DSHM), a cognitive model of associative memory that uses holographic reduced representations a...
Matthew Rutledge-Taylor, Andre Vellino, Robert L. ...