Vector algorithms allow the computation of an output vector r = r1r2 :::rm given an input vector e = e1e2 :::em in a bounded number of operations, independent of m the length of t...
We give an improved algorithm for computing personalized PageRank vectors with tight error bounds which can be as small as (n-p ) for any fixed positive integer p. The improved Pag...
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Computational resolution enhancement (superresolution) is generally regarded as a memory intensive process due to the large matrix-vector calculations involved. In this paper, a de...