Statistics Seminars: Parallel and Interacting Stochastic Approximation Annealing algorithms for global optimisation
17 October 2016 14:00 in CM221
We present the parallel and interacting stochastic approximation annealing (PISAA) algorithm, a stochastic simulation procedure for global optimisation, that extends and improves the stochastic approximation annealing (SAA) by using population Monte Carlo ideas. In high dimensional or rugged scenarios, the single chain SAA can present poor performance mainly because the target distribution is poorly adjusted. The proposed algorithm involves simulating a population of SAA chains that interact each other in a manner that ensures significant improvement of the self-adjusting mechanism and better exploration of the sampling space. We demonstrate the good performance of PISAA on challenging benchmark examples and applications such as protein folding, and our numerical comparisons suggest that PISAA outperforms other competitors.
Stochastic annealing, stochastic approximation, population MCMC, stochastic approximation annealing
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