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An Enhanced Extreme Learning Machine Based on Square-Root Lasso Method
Extreme learning machine (ELM) is one of the most notable machine learning algorithms with many advantages, especially its training speed. However,...
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DS-HECK: double-lasso estimation of Heckman selection model
We extend the Heckman (1979) sample selection model by allowing for a large number of controls that are selected using lasso under a sparsity...
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Coordinate descent algorithm for generalized group fused Lasso
We deal with a model with discrete varying coefficients to consider modeling for heterogeneity and clustering for homogeneity, and estimate the...
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Damage identification based on topology optimization and Lasso regularization
In this paper, we present a damage identification method for small damages based on topology optimization and Lasso regularization. In particular,...
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Using the Precision Lasso for gene selection in diffuse large B cell lymphoma cancer
BackgroundGene selection from gene expression profiles is the appropriate tool for diagnosing and predicting cancers. The aim of this study is to...
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Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology
In the current paper, we review existing tools for solving variable selection problems in psychology. Modern regularization methods such as lasso...
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Learning fused lasso parameters in portfolio selection via neural networks
In recent years, fused lasso models are becoming popular in several fields, such as computer vision, classification and finance. In portfolio...
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A New Type of LASSO Regression Model with Cauchy Noise
Many datasets have heavy-tailed behavior, and classical penalized models are not appropriate for them. To treat this problem, we propose a penalized...
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Self-regularized Lasso for selection of most informative features in microarray cancer classification
In this article, a new method is employed for maximizing the performance of the Least Absolute Shrinkage and Selection Operator (Lasso) feature...
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LASSO-derived model for the prediction of bleeding in aspirin users
Aspirin is widely used for both primary and secondary prevention of panvascular diseases, such as stroke and coronary heart disease (CHD). The...
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Bayesian penalization for explanatory cognitive diagnostic models: covariate DINA model and covariate LCDM with the lasso prior
Diagnostic assessment data obtained from online learning platforms for schools are typically accompanied by student background variables and item...
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Hybrid Approach for Streamflow Prediction: LASSO-Hampel Filter Integration with Support Vector Machines, Artificial Neural Networks, and Autoregressive Distributed Lag Models
The generation of streamflow is linked with different factors such as water level, rainfall intensity, meteorological variables, and many more. In...
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Two-Stage Online Debiased Lasso Estimation and Inference for High-Dimensional Quantile Regression with Streaming Data
In this paper, the authors propose a two-stage online debiased lasso estimation and statistical inference method for high-dimensional quantile...
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Adaptive Generalized Logistic Lasso and Its Application to Rankings in Sports
The generalized lasso is a popular model for ranking competitors, as it allows for implicit grou** of estimated abilities. In this work, we present...
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CEEMD-LASSO-ELM nonlinear combined model of air quality index prediction for four cities in China
Air pollution prevention and control is an important way to eliminate haze, and air quality prediction can provide predictive information for air...
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Improving Group Lasso for High-Dimensional Categorical Data
Sparse modeling or model selection with categorical data is challenging even for a moderate number of variables, because roughly one parameter is...
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Accounting for clustering in automated variable selection using hospital data: a comparison of different LASSO approaches
BackgroundAutomated feature selection methods such as the Least Absolute Shrinkage and Selection Operator (LASSO) have recently gained importance in...
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Spring precipitation forecasting with exhaustive searching and LASSO using climate teleconnection for drought management
Drought is defined as a prolonged regional precipitation deficiency. Significant drought conditions often occur during spring in South Korea since...
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Generalized regression estimators with concave penalties and a comparison to lasso type estimators
The generalized regression (GREG) estimator is usually used in survey sampling when incorporating auxiliary information. Generally, not all available...
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A novel and superior Lasso-plate technique in treatment for coronoid process fracture in the terrible triad of elbow
The treatment of ulna coronal process fractures in the terrible triad of elbow, especially type I and II Regan–Morrey coronoid fractures, still have...
