We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Narrowing was originally introduced to solve equational E-unification problems. It has also been recognized as a key mechanism to unify functional and logic programming. In both ...
Formal sequentialization is introduced as a rewriting process for the reduction of parallelism and internal communication statements of distributed imperative programs. It constru...
Miquel Bertran, Francesc-Xavier Babot, August Clim...
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
The pre-coloring extension problem consists, given a graph G and a set of nodes to which some colors are already assigned, in finding a coloring of G with the minimum number of co...