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Grouped Variable Selection with Discrete Optimization: Computational and
  Statistical Perspectives

Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives

14 April 2021
Hussein Hazimeh
Rahul Mazumder
P. Radchenko
ArXivPDFHTML

Papers citing "Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives"

16 / 16 papers shown
Title
Group COMBSS: Group Selection via Continuous Optimization
Group COMBSS: Group Selection via Continuous Optimization
Anant Mathur
S. Moka
Benoit Liquet
Z. Botev
36
0
0
20 Apr 2024
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with
  Combinatorial Optimization
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng
Shibal Ibrahim
Kayhan Behdin
Hussein Hazimeh
Natalia Ponomareva
Rahul Mazumder
VLM
41
5
0
02 Mar 2024
End-to-end Feature Selection Approach for Learning Skinny Trees
End-to-end Feature Selection Approach for Learning Skinny Trees
Shibal Ibrahim
Kayhan Behdin
Rahul Mazumder
27
0
0
28 Oct 2023
Performance of $\ell_1$ Regularization for Sparse Convex Optimization
Performance of ℓ1\ell_1ℓ1​ Regularization for Sparse Convex Optimization
Kyriakos Axiotis
T. Yasuda
25
0
0
14 Jul 2023
A minimax optimal approach to high-dimensional double sparse linear
  regression
A minimax optimal approach to high-dimensional double sparse linear regression
Yanhang Zhang
Zhifan Li
J. Yin
21
4
0
07 May 2023
Constrained Optimization of Rank-One Functions with Indicator Variables
Constrained Optimization of Rank-One Functions with Indicator Variables
Soroosh Shafieezadeh-Abadeh
Fatma Kılınç Karzan
21
4
0
31 Mar 2023
Variable Selection for Kernel Two-Sample Tests
Variable Selection for Kernel Two-Sample Tests
Jie Wang
Santanu S. Dey
Yao Xie
30
4
0
15 Feb 2023
The Directional Bias Helps Stochastic Gradient Descent to Generalize in
  Kernel Regression Models
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models
Yiling Luo
X. Huo
Y. Mei
11
0
0
29 Apr 2022
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
Hussein Hazimeh
Rahul Mazumder
Tim Nonet
13
12
0
10 Feb 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
Group selection and shrinkage: Structured sparsity for semiparametric
  additive models
Group selection and shrinkage: Structured sparsity for semiparametric additive models
Ryan Thompson
Farshid Vahid
10
1
0
25 May 2021
A Splicing Approach to Best Subset of Groups Selection
A Splicing Approach to Best Subset of Groups Selection
Yanhang Zhang
Junxian Zhu
Jin Zhu
Xueqin Wang
18
18
0
23 Apr 2021
Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is
  low
Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is low
Rahul Mazumder
P. Radchenko
Antoine Dedieu
13
57
0
10 Aug 2017
Correlated variables in regression: clustering and sparse estimation
Correlated variables in regression: clustering and sparse estimation
Peter Buhlmann
Philipp Rutimann
Sara van de Geer
Cun-Hui Zhang
80
181
0
26 Sep 2012
Oracle Inequalities and Optimal Inference under Group Sparsity
Oracle Inequalities and Optimal Inference under Group Sparsity
Karim Lounici
Massimiliano Pontil
Alexandre B. Tsybakov
Sara van de Geer
125
379
0
11 Jul 2010
High-dimensional additive modeling
High-dimensional additive modeling
L. Meier
Sara van de Geer
Peter Buhlmann
189
481
0
25 Jun 2008
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