LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
In this paper, we present a general and an efficient algorithm for automatic selection of new application-specific instructions under hardware resources constraints. The instructi...
Carlo Galuzzi, Elena Moscu Panainte, Yana Yankova,...
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
We consider a resource selection game with incomplete information about the resource-cost functions. All the players know is the set of players, an upper bound on the possible cos...