This paper presents a novel fault detection and section estimation method for unbalanced underground distribution systems (UDS). The method proposed is based on artificial neural n...
Karen Rezende Caino de Oliveira, Rodrigo Hartstein...
User preferences for automated assistance often vary widely, depending on the situation, and quality or presentation of help. Developing effective models to learn individual prefe...
We address the problem of improving the efficiency of natural language text input under degraded conditions (for instance, on mobile computing devices or by disabled users), by ta...
Abstract. The network measurement community has proposed multiple machine learning (ML) methods for traffic classification during the last years. Although several research works ha...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...