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

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

Machine learning time series regressions

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

Block coordinate descent for group lasso

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

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

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

Molecular-property prediction with sparsity

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

We explored various approaches to deal with high-dimensional data in this study, and we compared them using simulation and soil datasets. We discovered that grouping had a significant impact on model correctness and error reduction. For the core projection step, we first looked at the properties of all the algorithms and how they function to com…

HIWT-GSC: Homotopy Iterative Weighted Thresholding algorithm for solving Group Sparsity Constrained optimization problems

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

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

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