We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
3D scene understanding is key for the success of applications such as autonomous driving and robot navigation. However, existing approaches either produce a mild level of understa...
This paper is devoted to the blind separation of convolutive mixtures of possibly non circular linearly modulated signals with unknown (and possibly different) baud rates and carr...
Abstract—Coping with outliers contaminating dynamical processes is of major importance in various applications because mismatches from nominal models are not uncommon in practice...
Shahrokh Farahmand, Georgios B. Giannakis, Daniele...