1 code implementation • 4 Jul 2022 • Elias Wirth, Hiroshi Kera, Sebastian Pokutta
The vanishing ideal of a set of points $X = \{\mathbf{x}_1, \ldots, \mathbf{x}_m\}\subseteq \mathbb{R}^n$ is the set of polynomials that evaluate to $0$ over all points $\mathbf{x} \in X$ and admits an efficient representation by a finite subset of generators.
1 code implementation • 7 Feb 2022 • Elias Wirth, Sebastian Pokutta
To accommodate the noise in the data set, we introduce the Conditional Gradients Approximately Vanishing Ideal algorithm (CGAVI) for the construction of the set of generators of the approximately vanishing ideal.
no code implementations • 28 May 2021 • Christophe Roux, Elias Wirth, Sebastian Pokutta, Thomas Kerdreux
Several learning problems involve solving min-max problems, e. g., empirical distributional robust learning or learning with non-standard aggregated losses.
