Adaptive Threshold Sampling. (arXiv:1708.04970v2 [stat.ML] UPDATED)

Web: http://arxiv.org/abs/1708.04970

Sampling is a fundamental problem in computer science and statistics.
However, for a given task and stream, it is often not possible to choose good
sampling probabilities in advance. We derive a general framework for adaptively
changing the sampling probabilities via a collection of thresholds.In general,
adaptive sampling procedures introduce dependence amongst the sampled points,
making it difficult to compute expectations and ensure estimators are unbiased
or consistent. Our framework address this issue and further shows when adaptive
thresholds can …

arxiv ml sampling threshold