We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
We investigate the impact of input data scale in corpus-based learning using a study style of Zipf's law. In our research, Chinese word segmentation is chosen as the study ca...
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...