Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
For a reproduced sound field, the competing goals between the listening area and reproduction accuracy in an actual environment is one of the most important problems in sound fi...
How do users of virtual environments perceive virtual space? Many experiments have explored this question, but most of these have used head-mounted immersive displays. This paper ...
Eric Klein, J. Edward Swan II, Gregory S. Schmidt,...
Spatially coordinated packet sampling can be implemented by using a deterministic function of packet content to determine the selection decision for a given packet. In this way, a...
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...