A Regularization Approach to Nonlinear Variable Selection

By Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Alessandro Verri, Silvia Villa. 2010

29 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. Bharath K. Sriperumbudur
2. Zoltán Szabó
3. Krikamol Muandet
4. Lorenzo Rosasco
5. Alessandro Verri
6. Kenji Fukumizu
7. Arthur Gretton
8. Silvia Villa

Citations in the corpus

• Optimal Rates for Random Fourier Features (2015, background): “As motivated in Section 1, the question of approximating the derivatives of the kernel through finite dimensioal random feature map is also important as it enables to speed up several interesting machine learning tasks that involve the derivatives of the kernel (e.g., [32, 21, 17, 18, 29, 23]).”
• Nonparametric sparsity and regularization (2012, background): “Some preliminary results have appeared in a short conference version of this paper [49].”