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Pivot Selection for Dimension Reduction using Annealing by Increasing Resampling

In order to select an optimal set of pivots for dimension reduction, such as Simple-Map and sketches based on ball partitioning, we propose a method named Annealing by Increasing Resampling (AIR, for short). AIR assumes that every state is evaluated by using a sample set. Starting from an arbitrary initial state, AIR repeats to transit states by hill climbing, with evaluating the resampled sets whose size initially is small and gradually increases. Experiments verify that AIR can find better sets of pivots than the conventional method and in shorter time than simulated annealing.