Large-scale multipurpose cohort studies and biobanks often omit covariates needed for specific downstream analyses. We study target-population inference for generalized linear regression when key covariates are completely absent from the target data but observed in a related source population. Standard missing covariat...
Hua-Li Zhao, Kerstin Bunte Bernoulli Institute of Mathematics, Statistics et al.· 0 citations
Bayesian inference has become a standard tool for inferring stellar parameters from stellar evolution models. However, comparatively little attention has been paid to how alternative Bayesian likelihood formulations influence inferred stellar parameters, and the resulting evolutionary mass discrepancy for massive main...
C. I. Eze, G. Handler, M. Vanrespaille et al.· 0 citations
This work proposes a novel reduction method for Macaulay linear systems and derives a condition number lower bound incorporating a scaling factor, demonstrating that the optimized condition number translates directly into a reduction in circuit width, depth, and gate count.
Yu-Shen Han, Xue-Lian Li, Juntao Gao et al.· 0 citations
A novel semi-tensor product for third-order tensors under the t-product framework induced by arbitrary invertible linear transforms is introduced, yielding an accelerated multi-term randomized semi-tensor product SVD algorithm that achieves a balance between reconstruction accuracy and computational efficiency.
Xing-Chen Xiao, Feng Zhang, Wen-Jin Qin et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
