Four extensions of the universal law of robustness: log-concave covariates, heterogeneous mixtures, vector-valued predictors, and Markovian data
Read the original at arxiv.org→arXiv:2611.03653v1 Announce Type: new Abstract: Bubeck and Sellke's universal law of robustness says that fitting $n$ noisy samples below the noise level with a class of $p$ real parameters forces a Lipschitz...
Original headline: "Four Extensions of the Universal Law of Robustness: Log-Concave Covariates, Heterogeneous Mixtures, Vector-Valued Predictors, and Markovian Data"
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- Nov 4, 05:00 UTC arXiv cs.LG lead source Four Extensions of the Universal Law of Robustness: Log-Concave Covariates, Heterogeneous Mixtures, Vector-Valued Predictors, and Markovian Data