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

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

Molecular-property prediction with sparsity

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

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

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…

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

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

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