In this paper we propose a framework for learning a regression function form a set of local features in an image. The regression is learned from an embedded representation that re...
We developed a new model for iList, our system that helps students learn linked list. The model is automatically extracted from past student data, and allows iList to track student...
Davide Fossati, Barbara Di Eugenio, Stellan Ohlsso...
The transition from command-line interfaces to graphical interfaces has resulted in programs that are easier to learn and use, but harder to automate and reuse. Another transition...
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...
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...