We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
This paper compares Monte Carlo methods, lattice rules, and other low-discrepancy point sets on the problem of evaluating asian options. The combination of these methods with vari...
Abstract-In discrete detector PET, natural pixels are image basis functions calculated from responses of detector pairs. By using reconstruction with natural pixels the discretizat...
Charles L. Byrne, Stefaan Vandenberghe, Edward J. ...
—With the development of IC technology, it becomes urgent to investigate model reduction method for interconnects with process variations. In this paper, a one-shot projection al...
Jun Tao, Xuan Zeng, Fan Yang, Yangfeng Su, Lihong ...