— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
Resource discovery is an important process for finding suitable nodes that satisfy application requirements in large loosely-coupled distributed systems. Besides inter-node heter...
This paper proposes a method to compute the likelihood function for the amplitudes and phase shifts of noisily observed phase-locked and amplitude-constrained sinusoids. The sinus...
Christoph Reller, Hans-Andrea Loeliger, Stefano Ma...
Background subtraction is a widely used paradigm to detect moving objects in video taken from a static camera and is used for various important applications such as video surveill...