We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
This paper describes a pilot study of a computer simulation called WIIS, which is designed to extend students' learning experience of the sizes of the objects beyond human vi...
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Abstract. In this paper, several important issues related to visual motion analysis are addressed with a focus on the type of motion information to be estimated and the way context...