In the digital VLSI cycle, logic transformations are often required to modify the design to meet different synthesis and optimization goals. Logic transformations on sequential ci...
Yu-Shen Yang, Subarna Sinha, Andreas G. Veneris, R...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
—This paper addresses the problem of robust template tracking in image sequences. Our work falls within the discriminative framework in which the observations at each frame yield...
We propose a scalable face matching algorithm capable of dealing with faces subject to several concurrent and uncontrolled factors, such as variations in pose, expression, illumina...