no code implementations • ICML 2020 • Di Wang, Hanshen Xiao, Srini Devadas, Jinhui Xu
For this case, we propose a method based on the sample-and-aggregate framework, which has an excess population risk of $\tilde{O}(\frac{d^3}{n\epsilon^4})$ (after omitting other factors), where $n$ is the sample size and $d$ is the dimensionality of the data.
