Peer-reviewedLicence not statedBiometrika
Semiparametrically efficient semi-supervised statistical inference
- 1University of Washington Department of Biostatistics, , Box 351617, Seattle, Washington 98195, U.S.A
- 2University of Washington Departments of Statistics and Biostatistics, , Box 354322, Seattle, Washington 98195, U.S.A
- 3University of Washington Departments of Biostatistics and Statistics, , Box 351617, Seattle, Washington 98195, U.S.A
Related
- An Efficient Monte Carlo Method for Valid Prior-Free Possibilistic Statistical Inference
- HIFI: A Highly Efficient Framework for Statistical Inference with Foundation Models
- Semi-supervised learning on singular data sets
- Semi-Supervised Kernel Ridge Fréchet Regression
- Geometric Inductive Biases for Semi-Supervised Equalization: The Constellation-Aware Transformer
BibTeX
@article{xu2026semiparametrically,
title = {{Semiparametrically efficient semi-supervised statistical inference}},
author = {Zichun Xu and Daniela Witten and Ali Shojaie},
journal = {Biometrika},
year = {2026},
month = oct,
doi = {10.1093/biomet/asag050},
url = {http://arxiv.org/abs/2502.17741},
}
RIS
TY - JOUR
TI - Semiparametrically efficient semi-supervised statistical inference
AU - Zichun Xu
AU - Daniela Witten
AU - Ali Shojaie
PY - 2026
DA - 2026/10/28
JO - Biometrika
DO - 10.1093/biomet/asag050
UR - http://arxiv.org/abs/2502.17741
SN - 0006-3444
SN - 1464-3510
ER -