Abstract. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and contextfree languages to, in principle...
Traditional collision intensive multi-body simulations are difficult to control due to extreme sensitivity to initial conditions or model parameters. Furthermore, there may be mu...
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...
The ability to approximately answer aggregation queries accurately and efficiently is of great benefit for decision support and data mining tools. In contrast to previous sampling...
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...