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arXiv · 1002.5034

Threshold rules for online sample selection

Eric Bach·Shuchi Chawla·Seeun Umboh
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Abstract

We consider the following sample selection problem. We observe in an online fashion a sequence of samples, each endowed by a quality. Our goal is to either select or reject each sample, so as to maximize the aggregate quality of the subsample selected so far. There is a natural trade-off here between the rate of selection and the aggregate quality of the subsample. We show that for a number of such problems extremely simple and oblivious "threshold rules" for selection achieve optimal tradeoffs between rate of selection and aggregate quality in a probabilistic sense. In some cases we show that the same threshold rule is optimal for a large class of quality distributions and is thus oblivious in a strong sense.

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Eric Bach, Shuchi Chawla, Seeun Umboh. 2010-02-26. Threshold rules for online sample selection. https://arxiv.org/abs/1002.5034

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