Structured Sparsity: from Mixed Norms to Structured Shrinkage

By Matthieu Kowalski, Bruno Torrésani. 2009

58 citations recorded by the source corpus.

How researchers see this paper

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

1. Junzhou Huang
2. Shiwen Zhao
3. Tong Zhang
4. Francis R. Bach
5. Dimitris N. Metaxas
6. Chuan Gao
7. Barbara E. Engelhardt
8. Sayan Mukherjee

Citations in the corpus

• Bayesian group factor analysis with structured sparsity (2016, methodology): “The column-wise sparse structure of Λ in GFA models belongs to a general class of structured sparsity methods that has drawn attention recently (Zou and Hastie, 2005; Yuan and Lin, 2006; Jenatton et al., 2011, 2010; Kowalski, 2009; Kowalski and Torrésani, 2009; Zhao et al., 2009; Huang et al., 2011;”
• Learning with structured sparsity (2009, background): “In a related development [16], Kowalski et al. generalized the mixed norm penalty to structured shrinkage, which can identify the structured signi(cid:28)cance maps and thus can handle the case of the overlapping groups, However, the structured shrinkage operations do not necessarily convergence to…”