Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
We present a novel randomized approach to the graph isomorphism problem. Our algorithm aims at solving difficult instances by producing randomized certificates for non-isomorphis...
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Steganalysis in the wide sense consists of first identifying suspicious objects and then further analysis during which we try to identify the steganographic scheme used for embedd...
Jessica J. Fridrich, Miroslav Goljan, David Soukal