—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
The ability to associate images is the basis for learning relationships involving vision, hearing, tactile sensation, and kinetic motion. A new architecture is described that has ...
This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way. Currently, t...
Katrien Verbert, Dragan Gasevic, Jelena Jovanovic,...
Nonparametric Bayesian models are often based on the assumption that the objects being modeled are exchangeable. While appropriate in some applications (e.g., bag-ofwords models f...
Kurt T. Miller, Thomas L. Griffiths, Michael I. Jo...