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Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations

Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations

5 December 2015
Xiaohan Yan
Jacob Bien
ArXivPDFHTML

Papers citing "Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations"

6 / 6 papers shown
Title
The non-overlapping statistical approximation to overlapping group lasso
The non-overlapping statistical approximation to overlapping group lasso
Mingyu Qi
Tianxi Li
18
1
0
16 Nov 2022
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
Shibal Ibrahim
P. Radchenko
E. Ben-David
Rahul Mazumder
27
2
0
24 Aug 2021
A likelihood-based approach for multivariate categorical response
  regression in high dimensions
A likelihood-based approach for multivariate categorical response regression in high dimensions
Aaron J. Molstad
Adam J. Rothman
11
6
0
15 Jul 2020
Flexible co-data learning for high-dimensional prediction
Flexible co-data learning for high-dimensional prediction
M. V. van Nee
L. Wessels
M. A. van de Wiel
OOD
6
15
0
08 May 2020
Graph-Guided Banding of the Covariance Matrix
Graph-Guided Banding of the Covariance Matrix
Jacob Bien
11
6
0
01 Jun 2016
Learning Local Dependence In Ordered Data
Learning Local Dependence In Ordered Data
Guo Yu
Jacob Bien
14
34
0
25 Apr 2016
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