Kobak, D., Lomond, J., & Sanchez, B. (2018). Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization.
Chicago Style (17th ed.) CitationKobak, Dmitry, Jonathan Lomond, and Benoit Sanchez. Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative Due to the Implicit Ridge Regularization. 2018.
MLA (9th ed.) CitationKobak, Dmitry, et al. Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative Due to the Implicit Ridge Regularization. 2018.
Warning: These citations may not always be 100% accurate.