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Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm
Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical...
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A Dual Semismooth Newton Based Augmented Lagrangian Method for Large-Scale Linearly Constrained Sparse Group Square-Root Lasso Problems
Square-root Lasso problems have already be shown to be robust regression problems. Furthermore, square-root regression problems with structured...
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Evaluating methods for Lasso selective inference in biomedical research: a comparative simulation study
BackgroundVariable selection for regression models plays a key role in the analysis of biomedical data. However, inference after selection is not...
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On the Determination of Lagrange Multipliers for a Weighted LASSO Problem Using Geometric and Convex Analysis Techniques
Compressed Sensing (CS) encompasses a broad array of theoretical and applied techniques for recovering signals, given partial knowledge of their...
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A Method for Cancer Genomics Feature Selection Based on LASSO-RFE
A more efficient feature selection method was developed to screen genes corresponding to specific cancers to further investigate their pathogenesis....
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Applying logistic LASSO regression for the diagnosis of atypical Crohn's disease
In countries with a high incidence of tuberculosis, the typical clinical features of Crohn's disease (CD) may be covered up after tuberculosis...
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The priority of industrial sector coverage in China’s national emission trading system: an application of the LASSO model
This paper estimates the influences of different industries on the carbon prices and selects the industries with high market power in the carbon...
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A combined deep CNN-lasso regression feature fusion and classification of MLO and CC view mammogram image
Breast cancer is the most frequent disease among women, and it is a serious threat to their lives and well-being. Due to high population expansion,...
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Lasso-based variable selection methods in text regression: the case of short texts
Communication through websites is often characterised by short texts, made of few words, such as image captions or tweets. This paper explores the...
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Development and validation of a LASSO prediction model for cisplatin induced nephrotoxicity: a case-control study in China
BackgroundEarly identification of high-risk individuals with cisplatin-induced nephrotoxicity (CIN) is crucial for avoiding CIN and improving...
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LASSO-based nomogram predicts the risk factors of low anterior resection syndrome for middle and low rectal cancer underwent robotic surgery
BackgroundThis study aims to analyze the influencing factors of postoperative Low Anterior Resection Syndrome (LARS) in patients with middle and low...
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Easy surgical explantation technique for sutureless Perceval S prosthesis, ‘lasso technique’: a case report
BackgroundDue to structural valve deterioration of sutureless aortic prosthesis, there is a need for explantation of the prothesis. We introduce a...
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The prediction of Chongqing's GDP based on the LASSO method and chaotic whale group algorithm–back propagation neural network–ARIMA model
Accurate GDP forecasts are vital for strategic decision-making and effective macroeconomic policies. In this study, we propose an innovative approach...
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A composite quantile regression long short-term memory network with group lasso for wind turbine anomaly detection
Wind turbine anomaly detection is an important but challenging work. Though deep learning is promising in this filed, it may fail for large error...
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Geographically Weighted Sparse Group Lasso: Local and Global Variable Selections for GWR
This paper deals with the variable selection problem in geographically weighted regression (GWR). GWR is a local estimation method that continuously...
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Robust Moderately Clipped LASSO for Simultaneous Outlier Detection and Variable Selection
Outlier detection has become an important and challenging issue in high-dimensional data analysis due to the coexistence of data contamination and...
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The driving factors of corporate carbon emissions: an application of the LASSO model with survey data
Corporate carbon performance is a key driver of achieving corporate sustainability. The identification of factors that influence corporate carbon...
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The Lasso with Structured Design and Entropy of (Absolute) Convex Hulls
The paper [10] shows bounds for the prediction error of the Lasso. They use projection arguments to establish non-adaptive as well as adaptive...