We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class and the Lipschitz constant of the square root of the scalar loss function.
Jun 22, 2023
We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class and the Lipschitz ...
May 30, 2024 · We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class and the Lipschitz constant.
Jun 22, 2023 · Abstract. We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class ...
Jun 22, 2023 · We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class and the ...
Uniform Convergence with Square-Root Lipschitz Loss. Zhou, L., Dai, Z., Koehler, F., & Srebro, N. arXiv preprint, 2023. Uniform Convergence with Square-Root ...
Jun 22, 2023 · We establish generic uniform convergence guarantees for Gaussian data in terms of the Rademacher complexity of the hypothesis class and the ...
Jun 11, 2014 · There's no Lipschitz constant on [0,1]. If there were, then the derivative 1/2√x would be bounded, which is clearly false.
Missing: Loss. | Show results with:Loss.
Uniform Convergence with Square-Root Lipschitz Loss. Lijia Zhou, Zhen Dai, Frederic Koehler, and Nathan Srebro. In Advances in Neural Information Processing ...
May 4, 2020 · Lipschitz function and uniform convergence ... Given sequence of L−Lipschitz functions which converges pointwise, prove uniform convergence.
Missing: Square- Root Loss.