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...
Abstract. Monte Carlo (MC) methods have proved to be flexible, robust and very useful techniques in computational finance. Several studies have investigated ways to achieve greater...
Abstract. Games are considered important benchmark tasks of artificial intelligence research. Modern strategic board games can typically be played by three or more people, which m...
Monte Carlo based SSTA serves as the golden standard against alternative SSTA algorithms, but it is seldom used in practice due to its high computation time. In this paper, we acc...
Jason Cong, Karthik Gururaj, Wei Jiang, Bin Liu, K...
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...