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 technique for transforming classical approximation algorithms into constant-time algorithms that approximate the size of the optimal solution. Our technique is applic...
In this paper, we propose a method for robust kernel density estimation. We interpret a KDE with Gaussian kernel as the inner product between a mapped test point and the centroid ...
Evidence suggests that as software ages the original realizations of design patterns remain in place, and participants in design pattern realizations accumulate “grime” – no...
We believe it is unreasonable to assume that all students will own a laptop. One potential solution is to depend on the students to bring whatever computing devices (cell phones, ...