This paper explores the mathematical and algorithmic properties of two sample-based microtexture models: random phase noise (RPN ) and asymptotic discrete spot noise (ADSN ). Thes...
We present a new estimator for counting the number of solutions of a Boolean satisfiability problem as a part of an importance sampling framework. The estimator uses the recently...
We study the spatial-temporal sampling of a linear diffusion field, and show that it is possible to compensate for insufficient spatial sampling densities by oversampling in tim...
This paper studies Data Stream Management Systems that combine real-time data streams with historical data, and hence access incoming streams and archived data simultaneously. A s...
The vast size of real world stochastic programming instances requires sampling to make them practically solvable. In this paper we extend the understanding of how sampling affects ...