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

6 October 2009

Jianqing Fan

Jinchi Lv

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

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Title
Asymptotics for estimating a diverging number of parameters - with and without sparsity Jana Gauss Thomas Nagler 59 0 0 26 Nov 2024
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 J. F. Doriguello Debbie Lim Chi Seng Pun P. Rebentrost Tushar Vaidya 33 1 0 21 Dec 2023
Sparse Data-Driven Random Projection in Regression for High-Dimensional Data Roman Parzer Peter Filzmoser Laura Vana-Gur 19 2 0 30 Nov 2023
KOO approach for scalable variable selection problem in large-dimensional regression Z. Bai K. P. Choi Y. Fujikoshi Jiang Hu 11 1 0 30 Mar 2023
Stepdown SLOPE for Controlled Feature Selection Jingxuan Liang H. Chen Xuelin Zhang Weifu Li Xin Tang 65 0 0 21 Feb 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 32 8 0 02 Jan 2023
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 16 0 0 12 Oct 2022
Learning Acceptance Regions for Many Classes with Anomaly Detection Zhou Wang Xingye Qiao 11 0 0 20 Sep 2022
Error Controlled Feature Selection for Ultrahigh Dimensional and Highly Correlated Feature Space Using Deep Learning Arkaprabha Ganguli D. Todem T. Maiti OOD 11 0 0 15 Sep 2022
Sparse change detection in high-dimensional linear regression Fengnan Gao Tengyao Wang 19 4 0 12 Aug 2022
Provably tuning the ElasticNet across instances Maria-Florina Balcan M. Khodak Dravyansh Sharma Ameet Talwalkar 24 12 0 20 Jul 2022
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators Ziyan Yin 25 0 0 13 Jul 2022
A Statistical-Modelling Approach to Feedforward Neural Network Model Selection Andrew McInerney Kevin Burke 6 2 0 09 Jul 2022
Composite Expectile Regression with Gene-environment Interaction Jinghang Lin Yuan Huang Shuangge Ma 16 1 0 02 Jul 2022
Optimal Change-point Testing for High-dimensional Linear Models with Temporal Dependence Daren Wang Zifeng Zhao 19 5 0 08 May 2022
COMBSS: Best Subset Selection via Continuous Optimization S. Moka Benoit Liquet Hou-Ying Zhu Samuel Muller 14 5 0 05 May 2022
Error-based Knockoffs Inference for Controlled Feature Selection Xuebin Zhao H. Chen Yingjie Wang Weifu Li Tieliang Gong Yulong Wang Feng Zheng 22 1 0 09 Mar 2022
Flexible variable selection in the presence of missing data Brian D. Williamson Ying Huang 10 0 0 25 Feb 2022
Collective variable discovery in the age of machine learning: reality, hype and everything in between S. Bhakat AI4CE 24 24 0 06 Dec 2021
A Model-free Variable Screening Method Based on Leverage Score Wenxuan Zhong Yiwen Liu Peng Zeng 17 9 0 21 Sep 2021
Pre-processing with Orthogonal Decompositions for High-dimensional Explanatory Variables Xu Han Ethan X. Fang C. Tang 26 0 0 16 Jun 2021
Ultra High Dimensional Change Point Detection Xin Liu Liwen Zhang Zhen Zhang 14 0 0 09 Jun 2021
Bayesian subset selection and variable importance for interpretable prediction and classification Daniel R. Kowal 10 10 0 20 Apr 2021
$Asymptotic Theory of $\ell_1$-Regularized PDE Identification from a Single Noisy Trajectory$ Asymptotic Theory of $\ell_1$ -Regularized PDE Identification from a Single Noisy Trajectory Yuchen He Namjoon Suh X. Huo Sungha Kang Y. Mei 9 1 0 12 Mar 2021
Forward Stability and Model Path Selection N. Kissel L. Mentch 11 13 0 05 Mar 2021
Persistent Reductions in Regularized Loss Minimization for Variable Selection Amin Jalali 14 0 0 30 Nov 2020
Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network Qinzi Zhang Lewis Tseng 9 2 0 15 Nov 2020
Robust Finite Mixture Regression for Heterogeneous Targets Jian Liang Kun Chen Ming Lin Changshui Zhang Fei Wang 10 10 0 12 Oct 2020
How is Machine Learning Useful for Macroeconomic Forecasting? Philippe Goulet Coulombe Maxime Leroux D. Stevanovic Stéphane Surprenant 4 143 0 28 Aug 2020
On regularization methods based on Rényi's pseudodistances for sparse high-dimensional linear regression models E. Castilla A. Ghosh M. Jaenada Leandro Pardo 9 6 0 31 Jul 2020
How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning Yikai Wang Li Zhang Yuan Yao Yanwei Fu 24 43 0 15 Jul 2020
Functional Group Bridge for Simultaneous Regression and Support Estimation Zhengjia Wang J. Magnotti M. Beauchamp Meng Li 11 4 0 17 Jun 2020
Nested Model Averaging on Solution Path for High-dimensional Linear Regression Yang Feng Qingfeng Liu MoMe 12 5 0 16 May 2020
Variable Selection with Copula Entropy Jian Ma 10 11 0 28 Oct 2019
A Survey of Tuning Parameter Selection for High-dimensional Regression Y. Wu Lan Wang 29 35 0 10 Aug 2019
Analysis of overfitting in the regularized Cox model M. Sheikh Anthony C. C. Coolen 11 9 0 14 Apr 2019
Bayesian Factor-adjusted Sparse Regression Jianqing Fan Bai Jiang Qiang Sun 20 5 0 23 Mar 2019
Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data C. Wikle BDL 19 18 0 22 Feb 2019
Structure learning via unstructured kernel-based M-regression Xin He Yeheng Ge Xingdong Feng 22 0 0 03 Jan 2019
Strong consistency of the AIC, BIC, $C_p$ and KOO methods in high-dimensional multivariate linear regression Z. Bai Y. Fujikoshi Jiang Hu 8 5 0 30 Oct 2018
Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior Chang-rui Liu Yue Yang H. Bondell Ryan Martin 14 8 0 01 Oct 2018
Semiparametric model averaging for high dimensional conditional quantile prediction Jingwen Tu Hu Yang Chaohui Guo 13 2 0 05 Sep 2018
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking Fan Wang S. Mukherjee S. Richardson S. Hill 6 33 0 02 Aug 2018
Feature Learning and Classification in Neuroimaging: Predicting Cognitive Impairment from Magnetic Resonance Imaging Shan Shi F. Nathoo 11 0 0 17 Jun 2018
High-Dimensional Econometrics and Regularized GMM A. Belloni Victor Chernozhukov Denis Chetverikov Christian B. Hansen Kengo Kato 16 66 0 05 Jun 2018
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 Emre Demirkaya Yang Feng Pallavi Basu Jinchi Lv 8 0 0 17 Mar 2018
Nonparametric Independence Screening via Favored Smoothing Bandwidth Yang Feng Yichao Wu L. Stefanski 28 8 0 28 Nov 2017
Generalized Linear Model Regression under Distance-to-set Penalties Jason Xu Eric C. Chi K. Lange 18 36 0 03 Nov 2017