In this paper, we propose a new methodology for handling optimization problems with uncertain data. With the usual Robust Optimization paradigm, one looks for the decisions ensurin...
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Abstract. While a variety of multiple classifier systems have been studied since at least the late 1950's, this area came alive in the 90's with significant theoretical a...
Background: Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For examp...
Erwin P. Gianchandani, Matthew A. Oberhardt, Antho...
Abstract--We investigate a new approach to uplink communications in wideband outdoor cellular systems that can take advantage of multiple antennas at the base station in a scalable...