Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...
In many applications, replacing a complex word form by its stem can reduce sparsity, revealing connections in the data that would not otherwise be apparent. In this paper, we focu...
Shane Bergsma, Aditya Bhargava, Hua He, Grzegorz K...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Nowadays, wearable devices, such as mobile phones, PDAs, etc. gain widespread popularity for communication and data exchange. Consequently, several approaches investigate the prob...
Tasos Kontogiorgis, Dimitrios I. Fotiadis, Apostol...
—Governmental Transportation Authorities' interest in Car to Car and Car to Infrastructure has grown dramatically over the last few years in order to increase the road safet...
Raffaele Penazzi, Piergiorgio Capozio, Martin Dunc...