Some theoretical results on the Grouped Variables Lasso

By Christophe Chesneau, Mohamed Hebiri. 2008

62 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a5572ecac91158bea978d56a4341820ec2e4be2b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Alexandre B. Tsybakov
2. Tong Zhang
3. Sara A. van de Geer
4. Karim Lounici
5. Massimiliano Pontil
6. Mohamed Hebiri
7. Junzhou Huang
8. Francis R. Bach

In Statistics and Probability

1. Sara A. van de Geer
2. Alexandre B. Tsybakov
3. Tong Zhang
4. Massimiliano Pontil
5. Martin J. Wainwright
6. Karim Lounici
7. Mohamed Hebiri
8. Cun-Hui Zhang

Citations in the corpus

• Learning with structured sparsity (2009, background): “Several limitations of group Lasso were mentioned in [13].”
• The Smooth-Lasso and other ℓ1+ℓ2-penalized methods (2011, background): “This penalty has also been studied for example in [5, 15, 43].”
• Taking Advantage of Sparsity in Multi-Task Learning (2009, background): “Several papers analyzing statistical properties of the group Lasso appeared quite recently Bach [2008], Chesneau and Hebiri [2007], Huang et al. [2008], Koltchinskii and Yuan [2008], Meier et al. [2006, 2008], Nardi and Rinaldo [2008], Ravikumar et al. [2007].”