References in zbMATH (referenced in 10 articles )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Kim, Sun Hye; Boukouvala, Fani: Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques (2020)
  2. Adragni, Kofi P.; Karmakar, Moumita: A sequential test for variable selection in high dimensional complex data (2015)
  3. Shah, Jasmit; Datta, Somnath; Datta, Susmita: A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics (2014)
  4. Lock, Eric F.; Hoadley, Katherine A.; Marron, J. S.; Nobel, Andrew B.: Joint and individual variation explained (JIVE) for integrated analysis of multiple data types (2013)
  5. Marttinen, Pekka; Gillberg, Jussi; Havulinna, Aki; Corander, Jukka; Kaski, Samuel: Genome-wide association studies with high-dimensional phenotypes (2013)
  6. Yoshida, Hisako; Kawaguchi, Atsushi; Tsuruya, Kazuhiko: Radial basis function-sparse partial least squares for application to brain imaging data (2013)
  7. Chun, Hyonho; Keleş, Sündüz: Sparse partial least squares regression for simultaneous dimension reduction and variable selection (2010)
  8. Lykou, Anastasia; Whittaker, Joe: Sparse CCA using a lasso with positivity constraints (2010)
  9. Zhang, Dabao; Lin, Yanzhu; Zhang, Min: Penalized orthogonal-components regression for large (p) small (n) data (2009)
  10. Cao, Kim-Anh Lê; Rossouw, Debra; Robert-Granié, Christèle; Besse, Philippe: A sparse PLS for variable selection when integrating omics data (2008)