Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
Efficiently processing continuous k-nearest neighbor queries on data streams is important in many application domains, e. g. for network intrusion detection or in querysubscriber ...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
This paper proposes the methods to solve the constraint satisfaction problems (CSPs) using Q'tron neural networks (NNs). A Q'tron NN is local-minima free if it is built ...
Abstract. In this work one year hourly solar radiation data are analyzed and modeled. Using a 2-D surface fitting approach, a novel model is developed for the general behavior of ...