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cs.LG2026
Optimal Dimension-Free Sampling for Regularized Classification
Meysam Alishahi, Alexander Munteanu, Simon Omlor +1
We prove optimal sampling bounds achieving -relative error for a broad class of Lipschitz continuous classification loss functions under various regularization t…
cs.LG2026
Scalable Learning of Multivariate Distributions via Coresets
Zeyu Ding, Katja Ickstadt, Nadja Klein +2
Efficient and scalable non-parametric or semi-parametric regression analysis and density estimation are of crucial importance to the fields of statistics and machine learning. Howe…
cs.LG2024
Data subsampling for Poisson regression with pth-root-link
Han Cheng Lie, Alexander Munteanu
We develop and analyze data subsampling techniques for Poisson regression, the standard model for count data . In particular, we consider the Poisson generalized li…