We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...
We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...
As system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. For high-spee...
Carlos P. Coelho, Luis Miguel Silveira, Joel R. Ph...
A heuristic method to construct uniform approximations to analytic transcendental functions is developed as a generalization of the Hermite-Pad´e interpolation to infinite interv...