2018
Minimax lower bounds for function estimation on graphs
Publication
Publication
Electronic Journal of Statistics , Volume 12 - Issue 1 p. 651- 666
We study minimax lower bounds for function estimation problems on large graph when the target function is smoothly varying over the graph. We derive minimax rates in the context of regression and classification problems on graphs that satisfy an asymptotic shape assumption and with a smoothness condition on the target function, both formulated in terms of the graph Laplacian.
Additional Metadata | |
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doi.org/10.1214/18-EJS1407 | |
Electronic Journal of Statistics | |
Safe Bayesian Inference: A Theory of Misspecification based on Statistical Learning | |
Organisation | Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands |
Kirichenko, A., & van Zanten, H. (2018). Minimax lower bounds for function estimation on graphs. Electronic Journal of Statistics, 12(1), 651–666. doi:10.1214/18-EJS1407 |