Due to the limited amounts of on-chip memory, large volumes of data, and performance and power consumption overhead associated with interprocessor communication, efficient managem...
We present an adaptive out-of-core technique for rendering massive scalar volumes employing single pass GPU raycasting. The method is based on the decomposition of a volumetric dat...
—We present in this paper a general formulation for nonnegative data factorization, called projective nonnegative graph embedding (PNGE), which 1) explicitly decomposes the data ...
Dataset shift from the training data in a source domain to the data in a target domain poses a great challenge for many statistical learning methods. Most algorithms can be viewed ...
In this paper, we examine an emerging variation of the classification problem, which is known as the inverse classification problem. In this problem, we determine the features to b...