We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
— The growing interest in vehicular ad hoc networks (VANETs) enables decentralized traveler information systems to become more feasible and effective in Intelligent Transportatio...
We propose a probabilistic model for the Independent Vector Analysis approach to blind deconvolution and derive an asymptotic Newton method to estimate the model by Maximum Likelih...
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Mak...
Capacity estimation is an important part of covert channel analysis. It measures the severity of a covert channel by estimating the maximum information rate attainable over it. Tr...