Papers
My research is supported in part by the National Science Foundation (CAREER award DMS-1653017), the National Institutes of Health (R01 GM123993), and the Simons Foundation. Previously, my research was supported in part by a three-year grant from the National Science Foundation (NSF DMS-1405746).
Preprints
Publications
Sangwon Hyun, …, Jacob Bien (2022) Ocean Mover's Distance: Using Optimal Transport for Analyzing Oceanographic Data. Accepted, Proceedings of the Royal Society A [pdf] [code]
Sangwon Hyun, Mattias Rolf Cape, Francois Ribalet, and Jacob Bien (2022) Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions. Accepted, Annals of Applied Statistics [pdf] [software]
Daniel McDonald, Jacob Bien, et al. (2021) Can Auxiliary Indicators Improve COVID-19 Forecasting and Hotspot Prediction? Proceedings of the National Academy of Sciences 118(51) [pdf] [supplement] [code to reproduce all results]
Ines Wilms, Sumanta Basu, Jacob Bien, and David Matteson (2021) Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages. Accepted, Journal of the American Statistical Association [pdf] [software]
William Nicholson, Ines Wilms, Jacob Bien, and David Matteson (2020) High-Dimensional Forecasting via Interpretable Vector Autoregression. Journal of Machine Learning Research 21(166), 1−52. [pdf] [software]
Guo Yu, Jacob Bien, and Daniela Witten (2019) Discussion of “Covariate-assisted ranking and screening for large-scale two‐sample inference” Journal of the Royal Statistical Society, Series B. 81(2): 229-231. [paper] [supplement]
Jacob Bien, Irina Gaynanova, Johannes Lederer, and Christian Müller (2018) Prediction Error Bounds for Linear Regression With the TREX. TEST. 28, 451–474. [pdf]
Jacob Bien, Irina Gaynanova, Johannes Lederer, and Christian Müller (2016) Non-convex Global Minimization and False Discovery Rate Control for the TREX. Journal of Computational and Graphical Statistics. 27(1), 23-33. [pdf] [software]
William Nicholson, David Matteson, and Jacob Bien (2017) VARX-L: Structured Regularization for Large Vector Autoregressions with Exogenous Variables. International Journal of Forecasting. 33(3), 627-651 [pdf] [software]
Yin Lou, Jacob Bien, Rich Caruana, and Johannes Gehrke (2016) Sparse Partially Linear Additive Models. Journal of Computational and Graphical Statistics. 25(4), 1126-1140. [pdf] [software]
Jacob Bien, Florentina Bunea, and Luo Xiao (2016) Convex Banding of the Covariance Matrix. Journal of the American Statistical Association. 111(514), 834-845 [pdf] [software] [vignette]
Jacob Bien and Daniela Witten (2016) Penalized Estimation in Complex Models. In Bühlmann, Drineas, Kane, van der Laan (Eds.), Handbook of Big Data. Chapman and Hall/CRC
Reference.
[link]
Jacob Bien, Noah Simon, and Robert Tibshirani (2015) Convex Hierarchical Testing of Interactions. Annals of Applied Statistics. 9(1), 27-42. [pdf, supplement]
[software]
Jacob Bien, Jonathan Taylor, and Robert Tibshirani (2013) A Lasso for Hierarchical Interactions. Annals of Statistics.
41(3), 1111-1141 [pdf]
[software]
Robert Tibshirani, Jacob Bien, Jerome Friedman, Trevor Hastie,
Noah Simon, Jonathan Taylor, and Ryan Tibshirani (2012) Strong Rules for Discarding Predictors in Lasso-type Problems. Journal of the Royal Statistical Society, Series B. 74(2), 245-266
[pdf]
Neema Moraveji, Daniel Russell, Jacob Bien, David Mease (2011)
Measuring Improvement in User Search Performance Resulting from
Optimal Search Tips. Proceedings of SIGIR 2011.
[abstract]
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