—This paper addresses the problem of sparse recovery with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgrap...
We introduce the Tsallis divergence error measure in the context of pLSA matrix and tensor decompositions showing much improved performance in the presence of noise. The focus of ...
A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory which minimizes the resulting loss in mutual information. A divisive cl...
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
The problem of solving sparse Systems of Linear Algebraic Equations (SLAE) by parallel Monte Carlo numerical methods is considered. The almost optimal Monte Carlo algorithms are pr...