lasso_mex function Search Results


lasso_mex function  (MathWorks Inc)
90
MathWorks Inc lasso_mex function
Overview over hardware and software requirements of the different functions for estimating L1-regularized linear models. The <t> lasso function </t> is part of the Statistics and Machine Learning Toolbox and only included here for benchmarking purposes (see main text). The lasso_mex, lasso_mexcuda and lasso_gpu functions introduced here are specifically optimized for the mass-univariate analysis approach and depend on different hardware and software configurations
Lasso Mex Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/lasso_mex function/product/MathWorks Inc
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lasso_mex function - by Bioz Stars, 2026-04
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lasso_mex  (MathWorks Inc)
90
MathWorks Inc lasso_mex
Overview over hardware and software requirements of the different functions for estimating L1-regularized linear models. The <t> lasso function </t> is part of the Statistics and Machine Learning Toolbox and only included here for benchmarking purposes (see main text). The lasso_mex, lasso_mexcuda and lasso_gpu functions introduced here are specifically optimized for the mass-univariate analysis approach and depend on different hardware and software configurations
Lasso Mex, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/lasso_mex/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
lasso_mex - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

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Overview over hardware and software requirements of the different functions for estimating L1-regularized linear models. The lasso function is part of the Statistics and Machine Learning Toolbox and only included here for benchmarking purposes (see main text). The lasso_mex, lasso_mexcuda and lasso_gpu functions introduced here are specifically optimized for the mass-univariate analysis approach and depend on different hardware and software configurations

Journal: Neuroinformatics

Article Title: Fast Estimation of L1-Regularized Linear Models in the Mass-Univariate Setting

doi: 10.1007/s12021-020-09489-1

Figure Lengend Snippet: Overview over hardware and software requirements of the different functions for estimating L1-regularized linear models. The lasso function is part of the Statistics and Machine Learning Toolbox and only included here for benchmarking purposes (see main text). The lasso_mex, lasso_mexcuda and lasso_gpu functions introduced here are specifically optimized for the mass-univariate analysis approach and depend on different hardware and software configurations

Article Snippet: While the underlying coordinate descent algorithm is implemented in C++, the lasso_mex function can be conveniently called from Matlab via the mex API.

Techniques: Software