AllanJe/mahi

R package : Group lasso based selection for high-dimensional mediation analysis

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IntelLabs/distiller 📦

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller

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egpivo/QuantRegGLasso

R Package: Adaptively weighted group lasso for semiparametic quantile regression models

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ababii/Pythia.jl

Machine learning time series regressions

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jaredhuling/oem

Penalized least squares estimation using the Orthogonalizing EM (OEM) algorithm

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SzymonNowakowski/DMRnet Fork of cran/DMRnet

This is a development version of DMRnet — Delete or Merge Regressors Algorithms for Linear and Logistic Model Selection and High-Dimensional Data.

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AkexStar/Archived-group-lasso-optimization Fork of gzz2000/group-lasso-optimization 📦

本仓库归档弃用 移至https://github.com/AkexStar/Algorithms-group-LASSO-problem

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AkexStar/Algorithms-group-LASSO-problem

北大文再文-最优化方法（凸优化）-程序作业 Course homework for Optimization Methods 2023 Fall, PKU WenZW

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modal-inria/MLGL

Procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data

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stephenberg/bcd

Block coordinate descent for group lasso

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LamineTourelab/grpregOverlap Fork of YaohuiZeng/grpregOverlap

Regularization paths of linear, logistic, Poisson, or Cox models with overlapping grouped covariates

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sanjaradylov/sparse-cheml

Molecular-property prediction with sparsity

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charlotte0408/Research-about-ML-regularized-algorithms

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dankessler/608a-project

My project for STATS-608A in Fall 2018 at the University of Michigan

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