Statistics Theory and Methods

[16] Signed Support Recovery for Single Index Models in High-Dimensions

Neykov Matey Princeton University Qian Lin Harvard University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1701.333183

Annals of Mathematical Sciences and Applications, 1, (2), 379-426, 2016
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[17] On consistency and sparsity for sliced inverse regression in high dimensions

Qian Lin Harvard University Zhigen Zhao Temple University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1701.333182

Annals of statistics
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[18] Sparse Sliced Inverse Regression for High Dimensional Data

Qian Lin Harvard University Zhigen Zhao Temple University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1701.333181

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[19] On the optimality of sliced inverse regression in high dimensions

Qian Lin Harvard University Xinran Li Harvard University Dongming Huang Harvard University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1701.333180

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[20] Proper holomorphic embeddings of finitely connected planar domains into ℂ^{$n$}

Irena Majcen Mathematisches Institut, Alpeneggstrasse 22, Bern, Switzerland

Differential Geometry Geometric Analysis and Geometric Topology Statistics Theory and Methods mathscidoc:1701.10012

Arkiv for Matematik, 51, (2), 329-343, 2012.1
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