Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Many intelligent tutoring systems (ITSs) have been developed, deployed, assessed, and proven to facilitate learning. However, most of these systems do not generally adapt to new c...
The use of computer applications to support learning and assessment is becoming more common, along with a growing body of research focusing on the pedagogical effectiveness of the...
Recent research in visual inference from monocular images has shown that discriminatively trained image-based predictors can provide fast, automatic qualitative 3D reconstructions...
Atul Kanaujia, Cristian Sminchisescu, Dimitris N. ...