Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
We are developing an adaptive reminding system, which learns when and how to present notifications. In this paper, we focus on our XCS-based model, composed of two cascaded sets ...
This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of g...
Douglas J. Leith, William E. Leithead, Roderick Mu...
Many algorithm visualizations have been created, but little is known about which features are most important to their success. We believe that pedagogically useful visualizations ...
Purvi Saraiya, Clifford A. Shaffer, D. Scott McCri...