— Robotics applications based on computer vision algorithms are highly constrained to indoor environments where conditions may be controlled. The development of robust visual alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
— We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally corre...
The problem of dynamical tomography consists in reconstructing a temporal sequence of images from their noisy projections. For this purpose, a recursive algorithm is usually used,...
We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...