— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
: We present an automated detector that can predict a student’s future performance on a transfer post-test, a post-test involving related but different skills than the skills stu...
Ryan Shaun Joazeiro de Baker, Sujith M. Gowda, Alb...
We propose a novel approach to experience collection for autonomous service robots performing complex activities. This approach enables robots to data for many learning problems at...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Learning disabilities are serious societal problems contributing to a loss of quality of life for affected individuals and their families. We hypothesized that the learning disabil...
H. Craig Heller, Damien Colas, Norman F. Ruby, Fab...