Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
Perfect Information Monte Carlo (PIMC) search is a practical technique for playing imperfect information games that are too large to be optimally solved. Although PIMC search has ...
Jeffrey Richard Long, Nathan R. Sturtevant, Michae...
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,...
Increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. In this work, we propose a Monte-Carlo driven sto...
A novel stochastic searching scheme based on the Monte Carlo optimization is presented for polygonal approximation (PA) problem. We propose to combine the split-and-merge based lo...