References in zbMATH (referenced in 50 articles , 1 standard article )

Showing results 1 to 20 of 50.
Sorted by year (citations)

1 2 3 next

  1. Kang, Xiaoning; Kang, Lulu; Chen, Wei; Deng, Xinwei: A generative approach to modeling data with quantitative and qualitative responses (2022)
  2. Nguyen, Viet Anh; Kuhn, Daniel; Esfahani, Peyman Mohajerin: Distributionally robust inverse covariance estimation: the Wasserstein shrinkage estimator (2022)
  3. Pircalabelu, Eugen; Artemiou, Andreas: High-dimensional sufficient dimension reduction through principal projections (2022)
  4. Poignard, Benjamin; Fermanian, Jean-David: The finite sample properties of sparse M-estimators with pseudo-observations (2022)
  5. Banerjee, Samprit; Monni, Stefano: An orthogonally equivariant estimator of the covariance matrix in high dimensions and for small sample sizes (2021)
  6. Bradley, Jonathan R.: An approach to incorporate subsampling into a generic Bayesian hierarchical model (2021)
  7. Hong, Younghee; Chang, Iksoo; Kim, Choongrak: Detection of hubs in complex networks by the Laplacian matrix (2021)
  8. Kashlak, Adam B.: Non-asymptotic error controlled sparse high dimensional precision matrix estimation (2021)
  9. Kenney, Ana; Chiaromonte, Francesca; Felici, Giovanni: MIP-BOOST: efficient and effective (L_0) Feature selection for linear regression (2021)
  10. Krock, Mitchell; Kleiber, William; Becker, Stephen: Nonstationary modeling with sparsity for spatial data via the basis graphical Lasso (2021)
  11. Shen, Yuan; Zhang, Xingying; Zhang, Xiayang: A partial PPA block-wise ADMM for multi-block linearly constrained separable convex optimization (2021)
  12. Shen, Yuan; Zuo, Yannian; Yu, Aolin: A partially proximal S-ADMM for separable convex optimization with linear constraints (2021)
  13. Shen, Yuan; Zuo, Yannian; Zhang, Xiayang: A faster generalized ADMM-based algorithm using a sequential updating scheme with relaxed step sizes for multiple-block linearly constrained separable convex programming (2021)
  14. Tan, Lidan; Chiong, Khai Xiang; Moon, Hyungsik Roger: Estimation of high-dimensional seemingly unrelated regression models (2021)
  15. Wang, Shaoxin: An efficient numerical method for condition number constrained covariance matrix approximation (2021)
  16. Xu, Kai; Tian, Yan; Cheng, Qing: Testing regression coefficients in high-dimensional and sparse settings (2021)
  17. Yang, Yihe; Zhou, Jie; Pan, Jianxin: Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix (2021)
  18. Fan, Qingliang; Han, Xiao; Pan, Guangming; Jiang, Bibo: Large system of seemingly unrelated regressions: a penalized quasi-maximum likelihood estimation perspective (2020)
  19. Kang, Xiaoning; Xie, Chaoping; Wang, Mingqiu: A Cholesky-based estimation for large-dimensional covariance matrices (2020)
  20. Peeters, Carel F. W.; van de Wiel, Mark A.; van Wieringen, Wessel N.: The spectral condition number plot for regularization parameter evaluation (2020)

1 2 3 next