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Let me add an example from machine learning that shows that resorting to randomness is the optimal way, sometimes. When working on the whole data is not tractable (computation cost, data does not fit in memory), working on random samples can be an optimal way to train a machine learning algorithm. One of the most used optimization technique in those cases ...

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