Scalable bounding of predictive uncertainty in regression problems with SLAC
We propose SLAC, a sparse approximation to a Lipschitz constant estimator that can be utilised to obtain uncertainty bounds around predictions of a regression method. As we demonstrate in a series of experiments on real-world and synthetic data, this approach can yield fast and robust predictive unc...
| Main Authors: | , , , |
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| Format: | Conference item |
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Springer International Publishing
2018
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