We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Cognitive trait model (CTM) is a student model that aims to create profiles of learners’ cognitive traits. Divergent associative learning (DAL) denotes the characteristic of lea...