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Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
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Efficient Designs of SLOPE Penalty Sequences in Finite Dimension

International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
14 February 2021
Yiliang Zhang
Zhiqi Bu
ArXiv (abs)PDFHTML

Papers citing "Efficient Designs of SLOPE Penalty Sequences in Finite Dimension"

2 / 2 papers shown
Sparse Neural Additive Model: Interpretable Deep Learning with Feature
  Selection via Group Sparsity
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity
Shiyun Xu
Zhiqi Bu
Pratik Chaudhari
Ian Barnett
350
36
0
25 Feb 2022
Characterizing the SLOPE Trade-off: A Variational Perspective and the
  Donoho-Tanner Limit
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner LimitAnnals of Statistics (Ann. Stat.), 2021
Zhiqi Bu
Jason M. Klusowski
Cynthia Rush
Weijie J. Su
288
9
0
27 May 2021
1
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