Work

A framework to efficiently smooth L1 penalties for linear regression

Year: 2026

Type: article

Source: Computational Statistics

DOI: 10.1007/s00180-025-01710-6

Authors: Georg Hahn, Sharon M. Lutz, Nilanjana Laha, Julian Hecker, Dmitry Prokopenko, Sanghun Lee, Woojoo Lee, Michael H. Cho, Edwin K. Silverman, Christoph Lange

Institutions: Harvard University, Brigham and Women's Hospital, Massachusetts General Hospital, Dankook University, Seoul National University

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: Cure Alzheimer's Fund, National Heart, Lung, and Blood Institute, National Human Genome Research Institute

Awards: Systems Biology of Airway Disease, G4680013325, Physics of collective cellular migration in lung health and disease, (2 of 2) Genetic Epidemiology of COPD, (1 of 2) Genetic Epidemiology of COPD, Preparing Association Analysis Software Tools for Next Generation Sequencing Data, eMERGE Phase IV Clinical Center at Mass General Brigham

OpenAlex ID: W7131363750

FWCI:

Cites: 37

Cited by: 4

Related to: 10