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A Selective Overview of Variable Selection in High Dimensional Feature
  Space (Invited Review Article)

A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)

6 October 2009
Jianqing Fan
Jinchi Lv
ArXivPDFHTML

Papers citing "A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)"

50 / 132 papers shown
Title
Asymptotics for estimating a diverging number of parameters - with and
  without sparsity
Asymptotics for estimating a diverging number of parameters - with and without sparsity
Jana Gauss
Thomas Nagler
71
0
0
26 Nov 2024
TAVRNN: Temporal Attention-enhanced Variational Graph RNN Captures
  Neural Dynamics and Behavior
TAVRNN: Temporal Attention-enhanced Variational Graph RNN Captures Neural Dynamics and Behavior
M. Khajehnejad
Forough Habibollahi
Ahmad Khajehnejad
Brett J. Kagan
Adeel Razi
21
1
0
01 Oct 2024
Quantum Algorithms for the Pathwise Lasso
Quantum Algorithms for the Pathwise Lasso
J. F. Doriguello
Debbie Lim
Chi Seng Pun
P. Rebentrost
Tushar Vaidya
37
1
0
21 Dec 2023
Sparse Data-Driven Random Projection in Regression for High-Dimensional
  Data
Sparse Data-Driven Random Projection in Regression for High-Dimensional Data
Roman Parzer
Peter Filzmoser
Laura Vana-Gur
26
2
0
30 Nov 2023
KOO approach for scalable variable selection problem in
  large-dimensional regression
KOO approach for scalable variable selection problem in large-dimensional regression
Z. Bai
K. P. Choi
Y. Fujikoshi
Jiang Hu
21
1
0
30 Mar 2023
Stepdown SLOPE for Controlled Feature Selection
Stepdown SLOPE for Controlled Feature Selection
Jingxuan Liang
H. Chen
Xuelin Zhang
Weifu Li
Xin Tang
74
0
0
21 Feb 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Yikai Wang
Yanwei Fu
Xinwei Sun
NoLa
47
8
0
02 Jan 2023
Bregman Divergence-Based Data Integration with Application to Polygenic
  Risk Score (PRS) Heterogeneity Adjustment
Bregman Divergence-Based Data Integration with Application to Polygenic Risk Score (PRS) Heterogeneity Adjustment
Qinmengge Li
M. Patrick
Haihan Zhang
Chachrit Khunsriraksakul
P. Stuart
...
James T. Elder
Dajiang J. Liu
Jian Kang
L. Tsoi
Kevin He
32
0
0
12 Oct 2022
Learning Acceptance Regions for Many Classes with Anomaly Detection
Learning Acceptance Regions for Many Classes with Anomaly Detection
Zhou Wang
Xingye Qiao
19
0
0
20 Sep 2022
Error Controlled Feature Selection for Ultrahigh Dimensional and Highly
  Correlated Feature Space Using Deep Learning
Error Controlled Feature Selection for Ultrahigh Dimensional and Highly Correlated Feature Space Using Deep Learning
Arkaprabha Ganguli
D. Todem
T. Maiti
OOD
23
0
0
15 Sep 2022
Sparse change detection in high-dimensional linear regression
Sparse change detection in high-dimensional linear regression
Fengnan Gao
Tengyao Wang
32
4
0
12 Aug 2022
Provably tuning the ElasticNet across instances
Provably tuning the ElasticNet across instances
Maria-Florina Balcan
M. Khodak
Dravyansh Sharma
Ameet Talwalkar
42
12
0
20 Jul 2022
Communication-efficient Distributed Newton-like Optimization with
  Gradients and M-estimators
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators
Ziyan Yin
32
0
0
13 Jul 2022
A Statistical-Modelling Approach to Feedforward Neural Network Model
  Selection
A Statistical-Modelling Approach to Feedforward Neural Network Model Selection
Andrew McInerney
Kevin Burke
16
2
0
09 Jul 2022
Composite Expectile Regression with Gene-environment Interaction
Composite Expectile Regression with Gene-environment Interaction
Jinghang Lin
Yuan Huang
Shuangge Ma
23
1
0
02 Jul 2022
Optimal Change-point Testing for High-dimensional Linear Models with
  Temporal Dependence
Optimal Change-point Testing for High-dimensional Linear Models with Temporal Dependence
Daren Wang
Zifeng Zhao
35
6
0
08 May 2022
COMBSS: Best Subset Selection via Continuous Optimization
COMBSS: Best Subset Selection via Continuous Optimization
S. Moka
Benoit Liquet
Hou-Ying Zhu
Samuel Muller
23
6
0
05 May 2022
Error-based Knockoffs Inference for Controlled Feature Selection
Error-based Knockoffs Inference for Controlled Feature Selection
Xuebin Zhao
H. Chen
Yingjie Wang
Weifu Li
Tieliang Gong
Yulong Wang
Feng Zheng
34
1
0
09 Mar 2022
Flexible variable selection in the presence of missing data
Flexible variable selection in the presence of missing data
Brian D. Williamson
Ying Huang
19
0
0
25 Feb 2022
Collective variable discovery in the age of machine learning: reality,
  hype and everything in between
Collective variable discovery in the age of machine learning: reality, hype and everything in between
S. Bhakat
AI4CE
31
25
0
06 Dec 2021
A Model-free Variable Screening Method Based on Leverage Score
A Model-free Variable Screening Method Based on Leverage Score
Wenxuan Zhong
Yiwen Liu
Peng Zeng
20
9
0
21 Sep 2021
Pre-processing with Orthogonal Decompositions for High-dimensional
  Explanatory Variables
Pre-processing with Orthogonal Decompositions for High-dimensional Explanatory Variables
Xu Han
Ethan X. Fang
C. Tang
28
0
0
16 Jun 2021
Ultra High Dimensional Change Point Detection
Ultra High Dimensional Change Point Detection
Xin Liu
Liwen Zhang
Zhen Zhang
22
0
0
09 Jun 2021
Bayesian subset selection and variable importance for interpretable
  prediction and classification
Bayesian subset selection and variable importance for interpretable prediction and classification
Daniel R. Kowal
20
10
0
20 Apr 2021
Asymptotic Theory of $\ell_1$-Regularized PDE Identification from a
  Single Noisy Trajectory
Asymptotic Theory of ℓ1\ell_1ℓ1​-Regularized PDE Identification from a Single Noisy Trajectory
Yuchen He
Namjoon Suh
X. Huo
Sungha Kang
Y. Mei
21
1
0
12 Mar 2021
Forward Stability and Model Path Selection
Forward Stability and Model Path Selection
N. Kissel
L. Mentch
29
13
0
05 Mar 2021
Persistent Reductions in Regularized Loss Minimization for Variable
  Selection
Persistent Reductions in Regularized Loss Minimization for Variable Selection
Amin Jalali
23
0
0
30 Nov 2020
Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed
  Machine Learning Algorithm in Single-Hop Radio Network
Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network
Qinzi Zhang
Lewis Tseng
14
2
0
15 Nov 2020
Robust Finite Mixture Regression for Heterogeneous Targets
Robust Finite Mixture Regression for Heterogeneous Targets
Jian Liang
Kun Chen
Ming Lin
Changshui Zhang
Fei Wang
24
10
0
12 Oct 2020
How is Machine Learning Useful for Macroeconomic Forecasting?
How is Machine Learning Useful for Macroeconomic Forecasting?
Philippe Goulet Coulombe
Maxime Leroux
D. Stevanovic
Stéphane Surprenant
16
145
0
28 Aug 2020
On regularization methods based on Rényi's pseudodistances for sparse
  high-dimensional linear regression models
On regularization methods based on Rényi's pseudodistances for sparse high-dimensional linear regression models
E. Castilla
A. Ghosh
M. Jaenada
Leandro Pardo
23
6
0
31 Jul 2020
How to trust unlabeled data? Instance Credibility Inference for Few-Shot
  Learning
How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning
Yikai Wang
Li Zhang
Yuan Yao
Yanwei Fu
40
43
0
15 Jul 2020
Functional Group Bridge for Simultaneous Regression and Support
  Estimation
Functional Group Bridge for Simultaneous Regression and Support Estimation
Zhengjia Wang
J. Magnotti
M. Beauchamp
Meng Li
18
3
0
17 Jun 2020
Nested Model Averaging on Solution Path for High-dimensional Linear
  Regression
Nested Model Averaging on Solution Path for High-dimensional Linear Regression
Yang Feng
Qingfeng Liu
MoMe
22
5
0
16 May 2020
Variable Selection with Copula Entropy
Variable Selection with Copula Entropy
Jian Ma
28
11
0
28 Oct 2019
A Survey of Tuning Parameter Selection for High-dimensional Regression
A Survey of Tuning Parameter Selection for High-dimensional Regression
Y. Wu
Lan Wang
39
35
0
10 Aug 2019
Analysis of overfitting in the regularized Cox model
Analysis of overfitting in the regularized Cox model
M. Sheikh
Anthony C. C. Coolen
15
9
0
14 Apr 2019
Bayesian Factor-adjusted Sparse Regression
Bayesian Factor-adjusted Sparse Regression
Jianqing Fan
Bai Jiang
Qiang Sun
27
5
0
23 Mar 2019
Comparison of Deep Neural Networks and Deep Hierarchical Models for
  Spatio-Temporal Data
Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data
C. Wikle
BDL
32
19
0
22 Feb 2019
Structure learning via unstructured kernel-based M-regression
Structure learning via unstructured kernel-based M-regression
Xin He
Yeheng Ge
Xingdong Feng
31
0
0
03 Jan 2019
Strong consistency of the AIC, BIC, $C_p$ and KOO methods in
  high-dimensional multivariate linear regression
Strong consistency of the AIC, BIC, CpC_pCp​ and KOO methods in high-dimensional multivariate linear regression
Z. Bai
Y. Fujikoshi
Jiang Hu
20
5
0
30 Oct 2018
Bayesian inference in high-dimensional linear models using an empirical
  correlation-adaptive prior
Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior
Chang-rui Liu
Yue Yang
H. Bondell
Ryan Martin
26
8
0
01 Oct 2018
Semiparametric model averaging for high dimensional conditional quantile
  prediction
Semiparametric model averaging for high dimensional conditional quantile prediction
Jingwen Tu
Hu Yang
Chaohui Guo
25
2
0
05 Sep 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
24
33
0
02 Aug 2018
Feature Learning and Classification in Neuroimaging: Predicting
  Cognitive Impairment from Magnetic Resonance Imaging
Feature Learning and Classification in Neuroimaging: Predicting Cognitive Impairment from Magnetic Resonance Imaging
Shan Shi
F. Nathoo
13
0
0
17 Jun 2018
High-Dimensional Econometrics and Regularized GMM
High-Dimensional Econometrics and Regularized GMM
A. Belloni
Victor Chernozhukov
Denis Chetverikov
Christian B. Hansen
Kengo Kato
26
67
0
05 Jun 2018
Variable Selection via Adaptive False Negative Control in Linear
  Regression
Variable Selection via Adaptive False Negative Control in Linear Regression
X. J. Jeng
Xiongzhi Chen
13
9
0
20 Apr 2018
Large-Scale Model Selection with Misspecification
Large-Scale Model Selection with Misspecification
Emre Demirkaya
Yang Feng
Pallavi Basu
Jinchi Lv
14
0
0
17 Mar 2018
Nonparametric Independence Screening via Favored Smoothing Bandwidth
Nonparametric Independence Screening via Favored Smoothing Bandwidth
Yang Feng
Yichao Wu
L. Stefanski
35
8
0
28 Nov 2017
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
28
36
0
03 Nov 2017
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