Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
We present the Optimizing Control Variate (OCV) estimator, a new estimator for Monte Carlo rendering. Based upon a deterministic sampling framework, OCV allows multiple importance...
Shaohua Fan, Stephen Chenney, Bo Hu, Kam-Wah Tsui,...
We propose gate level statistical simulation to bridge the gap between the most accurate Monte Carlo SPICE simulation and the most efficient circuit level statistical static timi...