Best subset selection via a modern optimization lens
D Bertsimas, A King, R Mazumder - 2016 - projecteuclid.org
Best subset selection via a modern optimization lens Page 1 The Annals of Statistics 2016, Vol.
44, No. 2, 813–852 DOI: 10.1214/15-AOS1388 © Institute of Mathematical Statistics, 2016 …
44, No. 2, 813–852 DOI: 10.1214/15-AOS1388 © Institute of Mathematical Statistics, 2016 …
Regularized estimation in sparse high-dimensional time series models
S Basu, G Michailidis - 2015 - projecteuclid.org
Regularized estimation in sparse high-dimensional time series models Page 1 The Annals
of Statistics 2015, Vol. 43, No. 4, 1535–1567 DOI: 10.1214/15-AOS1315 © Institute of …
of Statistics 2015, Vol. 43, No. 4, 1535–1567 DOI: 10.1214/15-AOS1315 © Institute of …
Model selection for high-dimensional quadratic regression via regularization
Quadratic regression (QR) models naturally extend linear models by considering interaction
effects between the covariates. To conduct model selection in QR, it is important to maintain …
effects between the covariates. To conduct model selection in QR, it is important to maintain …
[PDF][PDF] Concave penalized estimation of sparse Gaussian Bayesian networks
We develop a penalized likelihood estimation framework to learn the structure of Gaussian
Bayesian networks from observational data. In contrast to recent methods which accelerate …
Bayesian networks from observational data. In contrast to recent methods which accelerate …
RANK: Large-scale inference with graphical nonlinear knockoffs
Power and reproducibility are key to enabling refined scientific discoveries in contemporary
big data applications with general high-dimensional nonlinear models. In this article, we …
big data applications with general high-dimensional nonlinear models. In this article, we …
Interaction pursuit in high-dimensional multi-response regression via distance correlation
Supplementary material to “Interaction pursuit in high-dimensional multi-response
regression via distance correlation”. Due to space constraints, the details about the post …
regression via distance correlation”. Due to space constraints, the details about the post …
IPAD: stable interpretable forecasting with knockoffs inference
Interpretability and stability are two important features that are desired in many
contemporary big data applications arising in statistics, economics, and finance. While the …
contemporary big data applications arising in statistics, economics, and finance. While the …
Divide-and-Conquer for Debiased -norm Support Vector Machine in Ultra-high Dimensions
1-norm support vector machine (SVM) generally has competitive performance compared to
standard 2-norm support vector machine in classification problems, with the advantage of …
standard 2-norm support vector machine in classification problems, with the advantage of …
Innovated interaction screening for high-dimensional nonlinear classification
Innovated interaction screening for high-dimensional nonlinear classification Page 1 The
Annals of Statistics 2015, Vol. 43, No. 3, 1243–1272 DOI: 10.1214/14-AOS1308 © Institute of …
Annals of Statistics 2015, Vol. 43, No. 3, 1243–1272 DOI: 10.1214/14-AOS1308 © Institute of …
Innovated scalable efficient estimation in ultra-large Gaussian graphical models
Innovated scalable efficient estimation in ultra-large Gaussian graphical models Page 1 The
Annals of Statistics 2016, Vol. 44, No. 5, 2098–2126 DOI: 10.1214/15-AOS1416 © Institute of …
Annals of Statistics 2016, Vol. 44, No. 5, 2098–2126 DOI: 10.1214/15-AOS1416 © Institute of …