We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
—We present a deterministic channel model which captures several key features of multiuser wireless communication. We consider a model for a wireless network with nodes connected...
Amir Salman Avestimehr, Suhas N. Diggavi, David N....
Hidden Markov Models (HMMs) are the most commonly used acoustic model for speech recognition. In HMMs, the probability of successive observations is assumed independent given the ...
This paper studies the in-band interference of time-hopping spread spectrum (TH-SS) ultra-wideband (UWB) signals to narrowband receivers. Based on the analysis of general power spe...
Dongsong Zeng, Amir I. Zaghloul, Annamalai Annamal...
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 ...