Monte Carlo Go is a promising method to improve the performance of computer Go programs. This approach determines the next move to play based on many Monte Carlo samples. This pap...
We present a simple new Monte Carlo algorithm for evaluating probabilities of observations in complex latent variable models, such as Deep Belief Networks. While the method is bas...
On-chip supply networks are playing an increasingly important role for modern nanometer-scale designs. However, the ever growing sizes of power grids make the analysis problem ext...
Abstract- Monte Carlo simulations have been successfully used in classic turn–based games such as backgammon, bridge, poker, and Scrabble. In this paper, we apply the ideas to th...
I will review the role that Monte Carlo methods play in the physical sciences. They are very widely used for a number of reasons: they permit the rapid and faithful transformation...
Our focus is on efficient estimation of tail probabilities of sums of correlated lognormals. This problem is motivated by the tail analysis of portfolios of assets driven by corre...
Jose Blanchet, Sandeep Juneja, Leonardo Rojas-Nand...
Much of the rare-event simulation literature is concerned with the development of asymptotically optimal algorithms. Because of the difficulties associated with applying these id...
The Monte Carlo and discrete-event simulation code associated with the Simulation 101 pre-conference workshop (offered at the 2006, 2007, and 2008 Winter Simulation Conferences) i...
Portfolio credit derivatives that depend on default correlation are increasingly widespread in the credit market. Valuing such products often entails Monte Carlo simulation. Howev...
Monte Carlo integration is a powerful technique for the evaluation of difficult integrals. Applications in rendering include distribution ray tracing, Monte Carlo path tracing, a...