In this paper, we consider a decision-maker who tries to learn the distribution of outcomes from previously observed cases. For each observed database of cases the decision-maker ...
Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
Abstract—This work proposes a novel approach - personalized forecasting - to take into account the sequential effect in predicting student performance (PSP). Instead of using all...
: In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...