We consider problems on data sets where each data point has uncertainty described by an individual probability distribution. We develop several frameworks and algorithms for calcul...
We define the computability of probability distributions on the real line as well as that of distribution functions. Mutual relationships between the computability notion of a pro...
—Finding the most likely path satisfying a requested additive Quality-of-Service (QoS) value, such as delay, when link metrics are defined as random variables by known probabili...
Information theory provides a range of useful methods to analyse probability distributions and these techniques have been successfully applied to measure information flow and the ...
Konstantinos Chatzikokolakis, Tom Chothia, Apratim...
This paper presents an approach to the analysis of task sets implemented on multiprocessor systems, when the task execution times are specified as generalized probability distrib...
We present a simulation-based semi-formal verification method for sequential circuits described at the registertransfer level. The method consists of an iterative loop where cove...
Serdar Tasiran, Farzan Fallah, David G. Chinnery, ...
Probability distributions are useful for expressing the meanings of probabilistic languages, which support formal modeling of and reasoning about uncertainty. Probability distribu...
As probabilistic computations play an increasing role in solving various problems, researchers have designed probabilistic languages that treat probability distributions as primit...
Abstract. We present an algorithm to generate samples from probability distributions on the space of curves. We view a traditional curve evolution energy functional as a negative l...
Ayres C. Fan, John W. Fisher III, William M. Wells...
The Earth Mover's distance was first introduced as a purely empirical way to measure texture and color similarities. We show that it has a rigorous probabilistic interpretati...