Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

标题
Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
作者
关键词
-
出版物
IEEE TRANSACTIONS ON INFORMATION THEORY
Volume 55, Issue 5, Pages 2183-2202
出版商
Institute of Electrical and Electronics Engineers (IEEE)
发表日期
2009-04-22
DOI
10.1109/tit.2009.2016018

向作者/读者发起求助以获取更多资源

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now