The OS* Algorithm: a Joint Approach to Exact Optimization and Sampling

By Marc Dymetman, Guillaume Bouchard, Simon Carter. 2012

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Most current sampling algorithms for high-dimensional distributions are based on MCMC techniques and are approximate in the sense that they are valid only asymptotically. Rejection sampling, on the other hand, produces valid samples, but is unrealistically slow in high-dimension spaces. The OS* algorithm that we propose is a unied approach to exact optimization and sampling, based on incremental renements

Subfields: Artificial Intelligence, Statistics and Probability, Optimization & Training, Probabilistic & Bayesian Methods