Statistics and Its Interface

Volume 11 (2018)

Number 3

Discussion on “Double sparsity kernel learning with automatic variable selection and data extraction”

Pages: 421 – 422



Yuan Huang (Department of Biostatistics, University of Iowa, Iowa City, Ia., U.S.A.)

Shuangge Ma (Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, U.S.A.)


Chen et al. (2018) presented a kernel learning method with double sparsity penalties to achieve variable selection and data extraction simultaneously. In this article, we highlight the authors’ contributions and provide several remarks that may be worth further discussions and exploration.


kernel learning, data extraction, variable selection, tuning parameter selection

Full Text (PDF format)

Received 2 March 2018