We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
—This paper considers the reconstruction of structured-sparse signals from noisy linear observations. In particular, the support of the signal coefficients is parameterized by h...
Algebraic randomization techniques can be applied to hybrid symbolic-numeric algorithms. Here we consider the problem of interpolating a sparse rational function from noisy values...
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Much recent work in the theoretical computer science, linear algebra, and machine learning has considered matrix decompositions of the following form: given an m
Petros Drineas, Michael W. Mahoney, S. Muthukrishn...