Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Most prior work on information extraction has focused on extracting information from text in digital documents. However, often, the most important information being reported in an...
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....