Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...

Autonomous Vehicles,Model Predictive Control,Lane Change,Intelligent Vehicles,Human Drivers,Object Detection,Automated Vehicles,Convolutional Neural Network,Optimal ...

Abstract: The proliferation of intelligent Internet of Things (IoT) applications has led to an increase in the complexity of tasks generated by IoT devices putting pressure on the timely execution of ...

Lorenzo Bruzzone (Fellow, IEEE) received the Laurea (M.S.) degree in electronic engineering (summa cum laude) and the Ph.D. degree in telecommunications from the University of Genoa, Genoa, Italy, in ...

Abstract: Interferometric synthetic aperture radar observations provide a means for obtaining high-resolution digital topographic maps from measurements of amplitude and phase of two complex radar ...

Abstract: Online learning is a well established learning paradigm which has both theoretical and practical appeals. The goal of online learning is to make a sequence of accurate predictions given ...

Also published under: Juan J. Rodriguez-Andina, J. J. Rodríguez-Andina, Juan Jose Rodriguez-Andina, J. J. Rodriguez-Andina, Juan Rodriguez-Andina, J. J. Rodriguez ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Book Abstract: This advanced text and reference covers the design and implementation of integrated circuits for analog-to-digital and digital-to-analog conversion. It begins with basic concepts and ...

Abstract: Problems involving the classical linear partial differential equations of mathematical physics can be reduced to algebraic ones of a very much simpler structure by replacing the ...

Abstract: The author was led to the study given in this paper from a consideration of large scale computing machines in which a large number of operations must be ...