In this paper we address the problem of searching in LZW compressed text directly, and present a new algorithm for finding multiple patterns by simulating the move of the Aho-Cora...
We describe a new LLL-type algorithm, H-LLL, that relies on Householder transformations to approximate the underlying Gram-Schmidt orthogonalizations. The latter computations are ...
We study the problem of adding k new links to a directed graph G(V, E) in order to maximize the minimum PageRank value for a given subset of the nodes. We show that this problem is...
We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...
The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...