# Universal Prediction Band via Semi-Definite Programming

@article{Liang2021UniversalPB, title={Universal Prediction Band via Semi-Definite Programming}, author={Tengyuan Liang}, journal={ArXiv}, year={2021}, volume={abs/2103.17203} }

We propose a computationally efficient method to construct nonparametric, heteroskedastic prediction bands for uncertainty quantification, with or without any user-speciﬁed predictive model. The data-adaptive prediction band is universally applicable with minimal distributional assumptions, with strong non-asymptotic coverage properties, and easy to implement using standard convex programs. Our approach can be viewed as a novel variance interpolation with confidence and further leverages…

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