Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Scenes with cast shadows can produce complex sets of
images. These images cannot be well approximated by lowdimensional
linear subspaces. However, in this paper we
show that the...
This is a theoretical study on the minimizers of cost-functions composed of an ℓ2 data-fidelity term and a possibly nonsmooth or nonconvex regularization term acting on the di...
The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...
In many fields where human understanding plays a crucial role, such as bioprocesses, the capacity of extracting knowledge from data is of critical importance. Within this framewor...