We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...
The intensive care unit is a challenging environment to both patient and caregiver. Continued shortages in staffing, principally in nursing, increase risk to patient and healthcar...
Brett L. Moore, Eric D. Sinzinger, Todd M. Quasny,...
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...