Name
Abstract | ||
|---|---|---|
This article presents a novel learning method based on componentwise Hölder continuity, which allows one to consider independently the contribution of each input to each output of the function to be learned. The method provides a bounded prediction error, and its learning property is proven. It can be used to obtain a predictor for a nonlinear robust learning-based predictive controller for constr... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TAC.2021.3056356 | IEEE Transactions on Automatic Control |
Keywords | DocType | Volume |
Learning systems,Predictive models,Estimation,Uncertainty,Standards,Prediction algorithms,Interpolation | Journal | 66 |
Issue | ISSN | Citations |
11 | 0018-9286 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José María Manzano | 1 | 0 | 0.34 |
| David Muñoz de la Peña | 2 | 293 | 24.98 |
| Jan-P. Calliess | 3 | 44 | 9.37 |
| Daniel Limon | 4 | 0 | 0.34 |