We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
In this paper, we present a mathematical theory for Marr's primal sketch. We first conduct a theoretical study of the descriptive Markov random field model and the generative...
We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionari...
We investigate the problem of reconstructing sparse multivariate trigonometric polynomials from few randomly taken samples by Basis Pursuit and greedy algorithms such as Orthogona...