We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
We present a novel approach to localization of objects in clutter images with the use of linear adaptive filters in a two-object classifier: target object versus clutter object. A...
The process by which outpatients are scheduled for a doctor's visit is a crucial determinant of the overall efficiency of the patient flow. The problem at hand consists of de...
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Excellent production design and planning depends on accurate simulation of a high quality layout. A good layout project will always begin with an analysis of the production volume...