A Regression Dependent Iterative Algorithm for Optimizing Top-K Selection in Simulation Query Language

In this paper the authors propose an extension of the algorithm General Optimal Regression Budget Allocation ScHeme GORBASH for iteratively optimizing simulation budget allocation while minimizing the total processing cost for top-k queries. They also implement this algorithm as part of SimQL: an extension of SQL that includes probability functions expressed through stochastic simulation.

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