Query-Adaptive Predictive Inference with Partial Labels. (arXiv:2206.07236v1 [stat.ML])

Web: http://arxiv.org/abs/2206.07236

The cost and scarcity of fully supervised labels in statistical machine
learning encourage using partially labeled data for model validation as a
cheaper and more accessible alternative. Effectively collecting and leveraging
weakly supervised data for large-space structured prediction tasks thus becomes
an important part of an end-to-end learning system. We propose a new
computationally-friendly methodology to construct predictive sets using only
partially labeled data on top of black-box predictive models. To do so, we
introduce "probe" functions as a way …

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