The Impact of Regularization on High-dimensional Logistic Regression

NeurIPS 2019 Fariborz SalehiEhsan AbbasiBabak Hassibi

Logistic regression is commonly used for modeling dichotomous outcomes. In the classical setting, where the number of observations is much larger than the number of parameters, properties of the maximum likelihood estimator in logistic regression are well understood... (read more)

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