In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
In this paper, we focus on methodology of finding a classifier with a minimal cost in presence of additional performance constraints. ROCCH analysis, where accuracy and cost are i...
—In a sensor network, in practice, the communication among sensors is subject to: 1) errors that can cause failures of links among sensors at random times; 2) costs; and 3) const...
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
Incorporating constraints into a reactive BDI agent programming language can lead to better expressive capabilities as well as more efficient computation (in some instances). More...