Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Time-sensitive network experiments are difficult. There are major challenges involved in generating high volumes of sufficiently realistic traffic. Additionally, accurately measur...
Neda Beheshti, Yashar Ganjali, Monia Ghobadi, Nick...
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
—With the ever increasing interest in multiple-input multiple-output (MIMO) cognitive radio (CR) systems, reducing the costs associated with RF-chains at the radio front end beco...
A set of sensors establishes barrier coverage of a given line segment if every point of the segment is within the sensing range of a sensor. Given a line segment I, n mobile sensor...
Jurek Czyzowicz, Evangelos Kranakis, Danny Krizanc...