Lazily adapted constant kinky inference for nonparametric regression and model-reference adaptive control
Techniques known as Nonlinear Set Membership prediction or Lipschitz Interpolation are approaches to supervised machine learning that utilise presupposed Lipschitz properties to perform inference over unobserved function values. Provided a bound on the true best Lipschitz constant of the target func...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2020
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