We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribut...
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...
It is well-known that opportunistic transmission schemes are sumcapacity optimal, in the Shannon sense, for symmetric cellular networks with single-antenna transceivers. However, ...
Pengcheng Zhan, Ramesh Annavajjala, A. Lee Swindle...
Several classification scenarios employ multiple independently trained classifiers and the outputs of these classifiers need to be combined. However, since each of the trained ...
— In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking in...