We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
We study revenue-maximizing pricing by a service provider in a communication network and compare revenues from simple pricing rules to the maximum revenues that are feasible. In pa...
Srinivas Shakkottai, R. Srikant, Asuman E. Ozdagla...
We introduce a method for approximate smoothed inference in a class of switching linear dynamical systems, based on a novel form of Gaussian Sum smoother. This class includes the ...
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
A powerful class of rate-compatible serially concatenated convolutional codes (SCCCs) has been proposed based on minimizing analytical upper bounds on the error probability in the ...