: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
To satisfy high-performance computing demand in modern embedded devices, current embedded processor architectures provide designer with possibility either to define customized ins...
I-Wei Wu, Zhi-Yuan Chen, Jean Jyh-Jiun Shann, Chun...
Multicore processors are an architectural paradigm shift that promises a dramatic increase in performance. But, they also bring an unprecedented level of complexity in algorithmic ...
Daniele Paolo Scarpazza, Oreste Villa, Fabrizio Pe...
The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared ...
Artur Loza, Fanglin Wang, Jie Yang, Lyudmila Mihay...
As superscalar processors become increasingly wide, it is inevitable that the large set of instructions to be fetched every cycle will span multiple noncontiguous basic blocks. Th...