Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference i...
In the present study a set of first order correlation functions are proposed to examine the quality of a wide class of identified nonlinear models. The first order correlation ...
We show the potential for classifying images of mixtures of aggregate, based themselves on varying, albeit well-defined, sizes and shapes, in order to provide a far more effective...
— Redistricting is the process of dividing a geographic area into districts or zones. This process has been considered in the past as a problem that is computationally too comple...
This paper studies optimal input excitation design for parametric frequency response estimation. We will focus on least-squares estimation of Finite Impulse Response (FIR) models a...