TOG
2012
12 years 3 months ago
2012
Procedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present Gabor noise by example, a method to estimate the ...
ISPD
2012
ACM
12 years 8 months ago
2012
ACM
Importance sampling is a popular approach to estimate rare event failures of SRAM cells. We propose to improve importance sampling by probability collectives. First, we use “Kul...
TOMACS
2002
14 years 11 days ago
2002
Consider the problem of estimating the small probability that the maximum of a random walk exceeds a large threshold, when the process has a negative drift and the underlying rand...
BMEI
2009
IEEE
14 years 1 months ago
2009
IEEE
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
UAI
2000
14 years 2 months ago
2000
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
WSCG
2004
14 years 2 months ago
2004
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
WSC
2004
14 years 2 months ago
2004
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
UAI
2008
14 years 2 months ago
2008
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
UAI
2008
14 years 2 months ago
2008
The paper introduces an AND/OR importance sampling scheme for probabilistic graphical models. In contrast to conventional importance sampling, AND/OR importance sampling caches sa...
WSC
2008
14 years 3 months ago
2008
We investigate the use of Antithetic Variables, Control Variates and Importance Sampling to reduce the statistical errors of option sensitivities calculated with the Likelihood Ra...