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Extended Comparisons of Best Subset Selection, Forward Stepwise
  Selection, and the Lasso
v1v2 (latest)

Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso

27 July 2017
Trevor Hastie
Robert Tibshirani
Ryan J. Tibshirani
ArXiv (abs)PDFHTML

Papers citing "Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso"

50 / 52 papers shown
Probabilistic and nonlinear compressive sensing
Probabilistic and nonlinear compressive sensing
Lukas Silvester Barth
Paulo von Petersenn
156
0
0
18 Sep 2025
An introduction to R package `mvs`
An introduction to R package `mvs`
Wouter van Loon
250
0
0
24 Apr 2025
Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age
Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age
Marcos Matabuena
173
0
0
12 Jan 2025
Classical Statistical (In-Sample) Intuitions Don't Generalize Well: A
  Note on Bias-Variance Tradeoffs, Overfitting and Moving from Fixed to Random
  Designs
Classical Statistical (In-Sample) Intuitions Don't Generalize Well: A Note on Bias-Variance Tradeoffs, Overfitting and Moving from Fixed to Random Designs
Alicia Curth
319
6
0
27 Sep 2024
Logistic Regression makes small LLMs strong and explainable
  "tens-of-shot" classifiers
Logistic Regression makes small LLMs strong and explainable "tens-of-shot" classifiers
Marcus Buckmann
Edward Hill
320
4
0
06 Aug 2024
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
Brian Liu
Rahul Mazumder
355
9
0
20 Feb 2024
Theoretical Analysis of Leave-one-out Cross Validation for
  Non-differentiable Penalties under High-dimensional Settings
Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
Haolin Zou
Arnab Auddy
Kamiar Rahnama Rad
A. Maleki
390
5
0
13 Feb 2024
Dynamic Incremental Optimization for Best Subset Selection
Dynamic Incremental Optimization for Best Subset Selection
Shaogang Ren
Xiaoning Qian
366
0
0
04 Feb 2024
Sparse Models for Machine Learning
Sparse Models for Machine Learning
Jia-Qi Lin
225
1
0
26 Aug 2023
Safe Peeling for L0-Regularized Least-Squares with supplementary
  material
Safe Peeling for L0-Regularized Least-Squares with supplementary material
Théo Guyard
Gilles Monnoyer
Clément Elvira
Cédric Herzet
227
1
0
28 Feb 2023
ControlBurn: Nonlinear Feature Selection with Sparse Tree Ensembles
ControlBurn: Nonlinear Feature Selection with Sparse Tree Ensembles
Brian Liu
Miao Xie
Haoyue Yang
Madeleine Udell
264
1
0
08 Jul 2022
Best Subset Selection with Efficient Primal-Dual Algorithm
Best Subset Selection with Efficient Primal-Dual Algorithm
Shaogang Ren
Guanhua Fang
P. Li
147
1
0
05 Jul 2022
Distributionally Robust Learning
Distributionally Robust Learning
Ruidi Chen
I. Paschalidis
OOD
446
77
0
20 Aug 2021
Principal Component Hierarchy for Sparse Quadratic Programs
Principal Component Hierarchy for Sparse Quadratic ProgramsInternational Conference on Machine Learning (ICML), 2021
R. Vreugdenhil
Viet Anh Nguyen
Armin Eftekhari
Peyman Mohajerin Esfahani
219
2
0
25 May 2021
Forward Stability and Model Path Selection
Forward Stability and Model Path SelectionStatistics and computing (Stat Comput), 2021
N. Kissel
L. Mentch
280
17
0
05 Mar 2021
Combinatorial Bayesian Optimization with Random Mapping Functions to
  Convex Polytopes
Combinatorial Bayesian Optimization with Random Mapping Functions to Convex PolytopesConference on Uncertainty in Artificial Intelligence (UAI), 2020
Jungtaek Kim
Seungjin Choi
Minsu Cho
313
6
0
26 Nov 2020
Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven
  Modeling of Air Pollutants
Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants
Javier Rubio-Herrero
Carlos Ortiz Marrero
W. Fan
122
11
0
13 Oct 2020
Estimation of Switched Markov Polynomial NARX models
Estimation of Switched Markov Polynomial NARX models
A. Brusaferri
Matteo Matteucci
S. Spinelli
123
1
0
29 Sep 2020
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing
  Kernel Krein Space and Indefinite Support Vector Machines
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines
A. Shilton
Sunil Gupta
Santu Rana
Svetha Venkatesh
260
0
0
15 Jul 2020
Simultaneous Feature Selection and Outlier Detection with Optimality
  Guarantees
Simultaneous Feature Selection and Outlier Detection with Optimality Guarantees
Luca Insolia
Ana M. Kenney
Francesca Chiaromonte
G. Felici
186
22
0
12 Jul 2020
Best subset selection is robust against design dependence
Best subset selection is robust against design dependence
Yongyi Guo
Ziwei Zhu
Jianqing Fan
260
9
0
03 Jul 2020
The Backbone Method for Ultra-High Dimensional Sparse Machine Learning
The Backbone Method for Ultra-High Dimensional Sparse Machine LearningMachine-mediated learning (ML), 2020
Dimitris Bertsimas
V. Digalakis
519
15
0
11 Jun 2020
Robust Grouped Variable Selection Using Distributionally Robust
  Optimization
Robust Grouped Variable Selection Using Distributionally Robust OptimizationJournal of Optimization Theory and Applications (JOTA), 2020
Ruidi Chen
I. Paschalidis
OOD
394
3
0
10 Jun 2020
Tree-Projected Gradient Descent for Estimating Gradient-Sparse
  Parameters on Graphs
Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on GraphsAnnual Conference Computational Learning Theory (COLT), 2020
Sheng Xu
Z. Fan
S. Negahban
199
0
0
31 May 2020
Additive stacking for disaggregate electricity demand forecasting
Additive stacking for disaggregate electricity demand forecasting
Christian Capezza
B. Palumbo
Y. Goude
S. Wood
Matteo Fasiolo
AI4TS
326
7
0
20 May 2020
Safe Screening Rules for $\ell_0$-Regression
Safe Screening Rules for ℓ0\ell_0ℓ0​-Regression
Alper Atamturk
A. Gómez
243
19
0
19 Apr 2020
Sparse Regression at Scale: Branch-and-Bound rooted in First-Order
  Optimization
Sparse Regression at Scale: Branch-and-Bound rooted in First-Order OptimizationMathematical programming (Math. Program.), 2020
Hussein Hazimeh
Rahul Mazumder
A. Saab
567
104
0
13 Apr 2020
A generalised OMP algorithm for feature selection with application to
  gene expression data
A generalised OMP algorithm for feature selection with application to gene expression data
M. Tsagris
Zacharias Papadovasilakis
Kleanthi Lakiotaki
Ioannis Tsamardinos
226
4
0
01 Apr 2020
Getting Better from Worse: Augmented Bagging and a Cautionary Tale of
  Variable Importance
Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable ImportanceJournal of machine learning research (JMLR), 2020
L. Mentch
Siyu Zhou
247
20
0
07 Mar 2020
Image denoising via K-SVD with primal-dual active set algorithm
Image denoising via K-SVD with primal-dual active set algorithmIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
Quan-Wu Xiao
Canhong Wen
Zirui Yan
136
0
0
19 Jan 2020
Graph Topological Aspects of Granger Causal Network Learning
Graph Topological Aspects of Granger Causal Network Learning
R. Kinnear
Ravi R. Mazumdar
CML
197
0
0
17 Nov 2019
Randomization as Regularization: A Degrees of Freedom Explanation for
  Random Forest Success
Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest SuccessJournal of machine learning research (JMLR), 2019
L. Mentch
Siyu Zhou
369
93
0
01 Nov 2019
Implicit Regularization for Optimal Sparse Recovery
Implicit Regularization for Optimal Sparse RecoveryNeural Information Processing Systems (NeurIPS), 2019
Tomas Vaskevicius
Varun Kanade
Patrick Rebeschini
225
115
0
11 Sep 2019
Directing Power Towards Conic Parameter Subspaces
Directing Power Towards Conic Parameter Subspaces
Nick W. Koning
426
1
0
11 Jul 2019
Sparse Unit-Sum Regression
Sparse Unit-Sum Regression
Nick W. Koning
P. Bekker
92
4
0
10 Jul 2019
Enhancing Multi-model Inference with Natural Selection
Enhancing Multi-model Inference with Natural Selection
Ching-Wei Cheng
Guang Cheng
213
1
0
06 Jun 2019
Machine Learning Methods Economists Should Know About
Machine Learning Methods Economists Should Know About
Susan Athey
Guido Imbens
296
828
0
24 Mar 2019
Rank-one Convexification for Sparse Regression
Rank-one Convexification for Sparse Regression
Alper Atamtürk
A. Gómez
444
50
0
29 Jan 2019
Optimization Problems for Machine Learning: A Survey
Optimization Problems for Machine Learning: A Survey
Claudio Gambella
Bissan Ghaddar
Joe Naoum-Sawaya
AI4CE
515
238
0
16 Jan 2019
Sparse and Smooth Signal Estimation: Convexification of L0 Formulations
Sparse and Smooth Signal Estimation: Convexification of L0 FormulationsJournal of machine learning research (JMLR), 2018
Alper Atamtürk
A. Gómez
Shaoning Han
382
48
0
06 Nov 2018
Feature Learning for Fault Detection in High-Dimensional
  Condition-Monitoring Signals
Feature Learning for Fault Detection in High-Dimensional Condition-Monitoring Signals
Gabriel Michau
Yang Hu
Thomas Palmé
Olga Fink
168
51
0
12 Oct 2018
High-dimensional regression in practice: an empirical study of
  finite-sample prediction, variable selection and ranking
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
Fan Wang
S. Mukherjee
S. Richardson
S. Hill
416
39
0
02 Aug 2018
Scalable Algorithms for the Sparse Ridge Regression
Scalable Algorithms for the Sparse Ridge Regression
Weijun Xie
Xinwei Deng
338
11
0
11 Jun 2018
Model selection with lasso-zero: adding straw to the haystack to better
  find needles
Model selection with lasso-zero: adding straw to the haystack to better find needles
Pascaline Descloux
S. Sardy
265
11
0
14 May 2018
Active Metric Learning for Supervised Classification
Active Metric Learning for Supervised Classification
K. Kumaran
Dimitri J. Papageorgiou
Yu-Ting Chang
Minhan Li
Martin Takáč
210
12
0
28 Mar 2018
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial
  Optimization Algorithms
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms
Hussein Hazimeh
Rahul Mazumder
709
204
0
05 Mar 2018
Generalized Linear Model Regression under Distance-to-set Penalties
Generalized Linear Model Regression under Distance-to-set Penalties
Jason Xu
Eric C. Chi
K. Lange
241
40
0
03 Nov 2017
Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is
  low
Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is lowOperational Research (OR), 2017
Rahul Mazumder
P. Radchenko
Antoine Dedieu
811
65
0
10 Aug 2017
A Robust Learning Algorithm for Regression Models Using Distributionally
  Robust Optimization under the Wasserstein Metric
A Robust Learning Algorithm for Regression Models Using Distributionally Robust Optimization under the Wasserstein Metric
Ruidi Chen
I. Paschalidis
OOD
203
1
0
07 Jun 2017
Forward-Backward Selection with Early Dropping
Forward-Backward Selection with Early DroppingJournal of machine learning research (JMLR), 2017
Giorgos Borboudakis
Ioannis Tsamardinos
386
112
0
30 May 2017
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