High-Dimensional Classification by Sparse Logistic Regression

DOI10.1109/TIT.2018.2884963zbMath1432.62177arXiv1706.08344OpenAlexW2963548292MaRDI QIDQ5223986

Vadim Grinshtein, Felix P. Abramovich

Publication date: 19 July 2019

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1706.08344

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12)

Related Items (6)

On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions ⋮ General Feasibility Bounds for Sample Average Approximation via Vapnik--Chervonenkis Dimension ⋮ Large Scale Prediction with Decision Trees ⋮ On the asymptotic properties of SLOPE ⋮ Optimal linear discriminators for the discrete choice model in growing dimensions ⋮ Global and Simultaneous Hypothesis Testing for High-Dimensional Logistic Regression Models

This page was built for publication: High-Dimensional Classification by Sparse Logistic Regression