Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Idle desktops have been successfully used to run sequential and master-slave task parallel codes on a large scale in the context of volunteer computing. However, execution of messa...
Nonlinear image reconstruction based upon sparse representations of images has recently received widespread attention with the emerging framework of compressed sensing (CS). This ...
Roummel F. Marcia, Zachary T. Harmany, Rebecca Wil...
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...