This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
Background: Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two met...
Daniel Restrepo-Montoya, Camilo Pino, Luis F. Ni&n...
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...