Matrices and Pictures
... There are a large number of pixels at the lower half of the integers, so these values are doubled. The upper half the integers can’t be doubled because the range would be larger than the domain of the colors, so they are set equal to one. Show Slide 9. (Slope) Edge Sharpening: Convolution Convolutio ...
... There are a large number of pixels at the lower half of the integers, so these values are doubled. The upper half the integers can’t be doubled because the range would be larger than the domain of the colors, so they are set equal to one. Show Slide 9. (Slope) Edge Sharpening: Convolution Convolutio ...
Matrix completion
In mathematics, matrix completion is the process of adding entries to a matrix which has some unknown or missing values.In general, given no assumptions about the nature of the entries, matrix completion is theoretically impossible, because the missing entries could be anything. However, given a few assumptions about the nature of the matrix, various algorithms allow it to be reconstructed. Some of the most common assumptions made are that the matrix is low-rank, the observed entries are observed uniformly at random and the singular vectors are separated from the canonical vectors. A well known method for reconstructing low-rank matrices based on convex optimization of the nuclear norm was introduced by Emmanuel Candès and Benjamin Recht.