This paper describes how soft performance bounds can be expressed for software systems using stochastic probes over stochastic process algebra models. These stochastic probes are ...
Ashok Argent-Katwala, Jeremy T. Bradley, Nicholas ...
A Bayesian marked point process (MPP) model is developed
to detect and count people in crowded scenes. The
model couples a spatial stochastic process governing number
and placem...
This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmenta...
In this paper, we present a robust method for estimating the model parameters in a mixture of probabilistic principal component analyzers. This method is based on the Stochastic v...
— Consider the following scenario: a spatio-temporal stochastic process generates service requests, localized at points in a bounded region on the plane; these service requests a...
Marco Pavone, Nabhendra Bisnik, Emilio Frazzoli, V...