LASSO Regression

LASSO regression, a method for fitting linear models by minimizing a penalized sum of squared errors, aims to select relevant variables and produce accurate predictions, particularly in high-dimensional settings. Current research focuses on improving LASSO's efficiency and applicability, including developing faster algorithms like block-coordinate descent and exploring its connections to deep neural networks, particularly in representing neural network training as equivalent LASSO problems. These advancements enhance LASSO's utility in diverse fields, from causal inference and time series analysis to recommender systems and online learning, by providing more efficient and robust solutions for high-dimensional data analysis.

Papers

October 23, 2024

Stabilizing black-box model selection with the inflated argmax
Melissa Adrian, Jake A. Soloff, Rebecca Willett
Black Box Model Model Selection Sparse Identification LASSO Regression

October 5, 2024

Black Boxes and Looking Glasses: Multilevel Symmetries, Reflection Planes, and Convex Optimization in Deep Networks
Emi Zeger, Mert Pilanci
Deep Neural Network Deep Network Black Box Convex Optimization Approximate Symmetry Shallow Network LASSO Regression

June 26, 2024

ROLCH: Regularized Online Learning for Conditional Heteroskedasticity
Simon Hirsch, Jonathan Berrisch, Florian Ziel
Online Estimation Distributional Model LASSO Regression

May 14, 2024

A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent
James Yang, Trevor Hastie
Standard LASSO Minimal Path Block Coordinate Descent Group Lasso LASSO Regression Regularization Path

May 5, 2024

Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection
Jingbo Liu
Financial Application Core Stability Variable Selection LASSO Regression Lasso Problem Lasso Condition Number

March 5, 2024

Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
Masahiro Kato
High Dimensional Causal Effect Conditional Average Treatment Effect Statistical Inference LASSO Regression

March 2, 2024

A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features
Emi Zeger, Yifei Wang, Aaron Mishkin, Tolga Ergen, Emmanuel Candès, Mert Pilanci
Deep Neural Network ReLU Network Etruscan Mirror LASSO Regression Deep Narrow Low Dimension

February 4, 2024

A Fast Method for Lasso and Logistic Lasso
Siu-Wing Cheng, Man Ting Wong
Compressed Sensing Standard LASSO LASSO Regression Sparse Reconstruction

December 19, 2023

The Convex Landscape of Neural Networks: Characterizing Global Optima and Stationary Points via Lasso Models
Tolga Ergen, Mert Pilanci
Neural Network Nonconvex Optimization Sparse Recovery Convex Program Global Optimum LASSO Regression Stationary Point Non Convex Landscape Convex Model

November 30, 2023

Piecewise Linearity of Min-Norm Solution Map of a Nonconvexly Regularized Convex Sparse Model
Yi Zhang, Isao Yamada
Sparse Model General Nonconvex Solution Space Sparse Regularization LASSO Regression Regularization Path

October 25, 2023

CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression
Masahiro Kato, Masaaki Imaizumi
High Dimensional Causal Inference Causal Effect Conditional Average Treatment Effect Standard LASSO LASSO Regression

September 7, 2023

Neural lasso: a unifying approach of lasso and neural networks
David Delgado, Ernesto Curbelo, Danae Carreras
Neural Network Machine Learning Cross Validation Variable Selection Unifying Theory Standard LASSO LASSO Regression Statistical Framework

May 30, 2023

Cooperative Thresholded Lasso for Sparse Linear Bandit
Haniyeh Barghi, Xiaotong Cheng, Setareh Maghsudi
Contextual Linear Bandit LASSO Regression Sparse Linear Bandit

May 17, 2023

On Consistency of Signatures Using Lasso
Xin Guo, Ruixun Zhang, Chaoyi Zhao
Strong Consistency Standard LASSO Handwritten Signature Stochastic Model LASSO Regression Signature Transform

September 22, 2022

Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach
Federico D'Amario, Milos Ciganovic
Sentiment Analysis Predictive Power Vector Autoregression LASSO Regression Social Medium Sentiment

June 29, 2022

Off-the-grid learning of sparse mixtures from a continuous dictionary
Cristina Butucea, Jean-François Delmas, Anne Dutfoy, Clément Hardy
Many Sparse Nonlinear Model LASSO Regression Finite Mixture Offline Model Based Optimization

June 20, 2022

Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
Jinkun Lin, Anqi Zhang, Mathias Lecuyer, Jinyang Li, Aurojit Panda, Siddhartha Sen
Deep Learning Model Training Data Mixed Effect Causal Inference Shapley Value Randomized Experiment LASSO Regression

May 21, 2022

Theoretically Accurate Regularization Technique for Matrix Factorization based Recommender Systems
Hao Wang
Recommender System Matrix Factorization Regularization Technique Regularization Based Method LASSO Regression

LASSO Regression

Papers

Stabilizing black-box model selection with the inflated argmax

Black Boxes and Looking Glasses: Multilevel Symmetries, Reflection Planes, and Convex Optimization in Deep Networks

ROLCH: Regularized Online Learning for Conditional Heteroskedasticity

A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent

Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection

Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects

A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features

A Fast Method for Lasso and Logistic Lasso

The Convex Landscape of Neural Networks: Characterizing Global Optima and Stationary Points via Lasso Models

Piecewise Linearity of Min-Norm Solution Map of a Nonconvexly Regularized Convex Sparse Model

CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression

Neural lasso: a unifying approach of lasso and neural networks

Cooperative Thresholded Lasso for Sparse Linear Bandit

On Consistency of Signatures Using Lasso

Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach

Off-the-grid learning of sparse mixtures from a continuous dictionary

Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments

Theoretically Accurate Regularization Technique for Matrix Factorization based Recommender Systems