The contribution of this paper is threefold. First, an improvement to a previously published paper on the timing analysis of Controller Area Network (CAN) in the presence of trans...
The task of identifying synonymous relations and objects, or Synonym Resolution (SR), is critical for high-quality information extraction. The bulk of previous SR work assumed str...
We describe a framework that helps students learn from examples by generating example problem solutions whose level of detail is tailored to the students' domain knowledge. T...
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...