Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
—As the operating frequency of digital systems increases and voltage swing decreases, it becomes very important to characterize and analyze power distribution networks (PDNs) acc...
Wendemagegnehu T. Beyene, Chuck Yuan, Joong-Ho Kim...
This paper suggests a discriminative approach for wavelet denoising
where a set of mapping functions (MF) are applied to the transform
coefficients in an attempt to produce a noi...
Nonuniform sampling of images is a useful technique in computer graphics, because a properly designed pattern of samples can make aliasing take the form of high-frequency random n...
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...