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Variable Selection for Efficient Design of Machine Learning-Based Models: Efficient Approaches for Industrial Applications

Engineering Applications of Neural Networks, p.352-366

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Effective Input Variable Selection for Function Approximation

Artificial Neural Networks – ICANN 2006, 2006, p.41-50

2006

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Sparse sliced inverse regression based on adaptive lasso penalty

AIP Conference Proceedings, 2022, Vol.2398 (1)

2022

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The Smoothly Clipped Absolute Deviation (SCAD) penalty variable selection regularization method for robust regression discontinuity designs

AIP Conference Proceedings, 2023, Vol.2776 (1)

2023

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Estimating Subject-Specific Treatment Differences for Risk-Benefit Assessment with Applications to Beta-Blocker Effectiveness Trials

Topics in Applied Statistics, p.75-86

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Sparse Projected Maximum Entropy Fuzzy c-Means

2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2024, p.1-9

2024

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Improving Featured-based Soft Sensing through Feature Selection

IFAC-PapersOnLine, 2020, Vol.53 (2), p.11338-11343

2020

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Variable Selection for Max-Affine Regression via Sparse Gradient Descent

2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM), 2024, p.1-5

2024

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Sparse PCA with False Discovery Rate Controlled Variable Selection

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, p.9716-9720

2024

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False Discovery Rate Control for Grouped Variable Selection in High-Dimensional Linear Models Using the T-Knock Filter

2022 30th European Signal Processing Conference (EUSIPCO), 2022, p.892-896

2022

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Variables selection which effecting on enlarged prostate gland by Bayesian Lasso quantile regression

AIP Conference Proceedings, 2023, Vol.2845 (1)

2023

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Variable selection of yearly high dimension stock market price using ordered homogenous pursuit lasso

AIP Conference Proceedings, 2020, Vol.2266 (1)

2020

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Using SOM-Based Data Binning to Support Supervised Variable Selection

Lecture notes in computer science, 2004, p.172-180

2004

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A variable selection and structure optimization algorithm for online sequence extreme learning machine

2022 13th Asian Control Conference (ASCC), 2022, p.482-487

2022

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A Novel Variable Selection Algorithm for Soft Sensor Using Gated Recurrent Unit and Garrote Variable Attention Mechanism

2023 42nd Chinese Control Conference (CCC), 2023, p.6644-6649

2023

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Variable Selection Method Based on Least Absolute Shrinkage and Selection Operator (LASSO) and kNN for Faults Isolation

2022 41st Chinese Control Conference (CCC), 2022, p.4069-4074

2022

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Sparsity Constraint Implementation for the Joint Eigenvalue Decomposition of Matrices

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023, p.1-5

2023

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Identifying Variables to Define Innovator Group in the Healthy Food Industry: A Fuzzy Approach

Artificial Intelligence XXXV, p.440-445

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Alternative approach to identify active effects in supersaturated experiments

AIP Conference Proceedings, 2019, Vol.2192 (1)

2019

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Development of input variable selection and structural optimization algorithm for recurrent neural network

2021 40th Chinese Control Conference (CCC), 2021, p.8094-8099

2021

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Recovering the Graphical Structures via Knockoffs

Procedia computer science, 2018, Vol.129, p.201-207

2018

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Sparse Reduced-Rank Regression With Adaptive Selection of Groups of Predictors

2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021, p.145-149

2021

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Development of a novel variable selection algorithm for LSTM with LASSO

2021 40th Chinese Control Conference (CCC), 2021, p.8222-8227

2021

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DEVELOPING TRANSFERABLE SPATIAL PREDICTION MODELS: A CASE STUDY OF SATELLITE BASED LANDCOVER MAPPING

International archives of the photogrammetry, remote sensing and spatial information sciences., 2022, Vol.XLIII-B3-2022, p.135-141

2022

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A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models

Multiple Classifier Systems, p.3-14

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Variable Selection for Efficient Design of Machine Learning-Based Models: Efficient Approaches for Industrial Applications

Effective Input Variable Selection for Function Approximation

Sparse sliced inverse regression based on adaptive lasso penalty

The Smoothly Clipped Absolute Deviation (SCAD) penalty variable selection regularization method for robust regression discontinuity designs

Estimating Subject-Specific Treatment Differences for Risk-Benefit Assessment with Applications to Beta-Blocker Effectiveness Trials

Sparse Projected Maximum Entropy Fuzzy c-Means

Improving Featured-based Soft Sensing through Feature Selection

Variable Selection for Max-Affine Regression via Sparse Gradient Descent

Sparse PCA with False Discovery Rate Controlled Variable Selection

False Discovery Rate Control for Grouped Variable Selection in High-Dimensional Linear Models Using the T-Knock Filter

Variables selection which effecting on enlarged prostate gland by Bayesian Lasso quantile regression

Variable selection of yearly high dimension stock market price using ordered homogenous pursuit lasso

Using SOM-Based Data Binning to Support Supervised Variable Selection

A variable selection and structure optimization algorithm for online sequence extreme learning machine

A Novel Variable Selection Algorithm for Soft Sensor Using Gated Recurrent Unit and Garrote Variable Attention Mechanism

Variable Selection Method Based on Least Absolute Shrinkage and Selection Operator (LASSO) and kNN for Faults Isolation

Sparsity Constraint Implementation for the Joint Eigenvalue Decomposition of Matrices

Identifying Variables to Define Innovator Group in the Healthy Food Industry: A Fuzzy Approach

Alternative approach to identify active effects in supersaturated experiments

Development of input variable selection and structural optimization algorithm for recurrent neural network

Recovering the Graphical Structures via Knockoffs

Sparse Reduced-Rank Regression With Adaptive Selection of Groups of Predictors

Development of a novel variable selection algorithm for LSTM with LASSO

DEVELOPING TRANSFERABLE SPATIAL PREDICTION MODELS: A CASE STUDY OF SATELLITE BASED LANDCOVER MAPPING

A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models

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