Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Abstract—With the growing complexity of software applications, there is an increasing demand for solutions to distribute workload into server pools. Grid Computing provides power...
Xing Zhou, Thomas Dreibholz, Martin Becke, Jobin P...
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
—This paper deals with the problem of estimating the steering direction of a signal, embedded in Gaussian disturbance, under a general quadratic inequality constraint, representi...
Abstract. Task-structured probabilistic input/output automata (taskPIOAs) are concurrent probabilistic automata that, among other things, have been used to provide a formal framewo...
Aaron D. Jaggard, Catherine Meadows, Michael Mislo...