When viewed from a system of multiple cameras with nonoverlapping fields of view, the appearance of an object in one camera view is usually very different from its appearance in a...
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
We propose a new probabilistic approach to information retrieval based upon the ideas and methods of statistical machine translation. The central ingredient in this approach is a ...
This paper describes a study in which individual learner models were built for students and presented to them with a choice of view. Students found it useful, and not confusing to ...
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...