An Analysis of Random Design Linear Regression

By Daniel J. Hsu, Sham M. Kakade, Tong Zhang. 2011

36 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. Sham M. Kakade
2. Daniel J. Hsu
3. Francis R. Bach
4. Tong Zhang
5. Sergey Levine
6. Alekh Agarwal
7. Yoshua Bengio
8. Prateek Jain

Citations in the corpus

• Finding and Leveraging Structure in Learning Problems (2012, background): “There is also a large literature with sharp characterization of risk bounds for linear regression [Hsu et al., 2011, Dhillon et al., 2011, Audibert and Catoni, 2010].”
• Tail inequalities for sums of random matrices that depend on the intrinsic dimension (2012, methodology): “…on the explicit matrix dimension (this is reviewed in Section 3.3), which prevents their application to infinite dimensional spaces that arise in a variety of data analysis tasks (e.g., Schölkopf et al., 1999; Rasmussen and Williams, 2006; Fukumizu et al., 2007; Bach, 2008; Hsu et al., 2011).”