Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers...
Although Bayesian model averaging is theoretically the optimal method for combining learned models, it has seen very little use in machine learning. In this paper we study its app...
The diffusion orientation transform (DOT) enables the computation of orientational probability profiles from high angular resolution diffusion-weighted magnetic resonance imaging ...
Today, the choice for a particular programming language limits the alternative products that can be used to deploy the program. The purpose of this work is to break the strong tie...
Hotkeys are extremely useful in leveraging expert performance, but learning them is a slow process. This paper investigates alternative menu designs that can motivate and help use...
Tovi Grossman, Pierre Dragicevic, Ravin Balakrishn...