Assistant Professor I enjoy working on problems in statistical machine learning and applied statistics, especially developing methods that might be of direct use to scientists (or others with large datasets). A particular interest of mine is in using convex optimization to tackle the challenges of high-dimensional datasets. |
Guo Yu and Jacob Bien (2016) Learning Local Dependence In Ordered Data. [pdf]
Jacob Bien, Irina Gaynanova, Johannes Lederer, and Christian Müller (2016) Non-convex Global Minimization and False Discovery Rate Control for the TREX. [pdf] [software]
Xiaohan Yan and Jacob Bien (2015) Hierarchical Sparse Modeling: A Choice of Two Regularizers. [pdf]
William Nicholson, David Matteson, and Jacob Bien (2015) VARX-L: Structured Regularization for Large Vector Autoregressions with Exogenous Variables. [pdf]
William Nicholson, Jacob Bien, and David Matteson (2014) Hierarchical Vector Autoregression. [pdf]
Yin Lou, Jacob Bien, Rich Caruana, and Johannes Gehrke (2014) Sparse Partially Linear Additive Models. Accepted to Journal of Computational and Graphical Statistics. [pdf] [software]
Jacob Bien, Florentina Bunea, and Luo Xiao (2014) Convex Banding of the Covariance Matrix. Accepted to Journal of the American Statistics Association. [pdf] [software] [vignette]
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]
Jacob Bien and Marten Wegkamp (2013) Discussion of “Correlated variables in regression: clustering and sparse estimation” by Bühlmann et al. Journal of Statistical Planning and Inference. 143(11), 1859-1862. [pdf]
Jacob Bien and Robert Tibshirani (2011) Hierarchical Clustering with Prototypes via Minimax Linkage. Journal of the American Statistical Association. 106(495). 1075-1084 [pdf] [software]
Jacob Bien and Robert Tibshirani (2011) Sparse Estimation of a Covariance Matrix. Biometrika. 98(4). 807-820 [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]
Jacob Bien and Robert Tibshirani (2011) Prototype Selection for Interpretable Classification. Annals of Applied Statistics. 5(4). 2403-2424 [pdf] [software]
Jacob Bien, Ya Xu, and Michael Mahoney (2010) CUR from a Sparse Optimization Viewpoint. Advances in Neural Information Processing Systems 23. [pdf]
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]
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]
BTRY 7180: Generalized Linear Models (Spring 2016)
BTRY/STSCI 4090: Theory of Statistics (Spring 2016)
BTRY/STSCI 4090: Theory of Statistics (Spring 2015)
BTRY 6010: Statistical Methods I (Fall 2014)
BTRY/STSCI 4090: Theory of Statistics (Spring 2014)
BTRY 4950/7950: Statistical Consulting (Spring 2014)
BTRY 7180: Generalized Linear Models (Fall 2013)
BTRY/STSCI 4090: Theory of Statistics (Spring 2013)
For CVX users: Here is an R package I wrote to call CVX from R.
New: For those who prefer Julia to MATLAB (but use R primarily), I've just written convexjulia, an R package for using Convex.jl.
I enjoy juggling. Here are some videos of me club passing with the Stanford Court Jugglers. I am to the far left in this video and this video and am in the front right in this video (if you look closely, you'll notice that every pass I throw is to the person behind me).
Here's my solution to an incredible physics puzzle involving elastic collisions and the digits of pi. I wrote this up in the summer of 2010, after hearing the problem from Caitlin Stanton and Tucker Hiatt. Section 1 states the problem. My favorite part is Section 6, which gives a simple explanation for the link between having constant kinetic energy and pi.
Phone: 607-255-7011
Fax: 607-255-4698
Address:
Department of Biological Statistics and Computational Biology
1178 Comstock Hall
Cornell University
Ithaca, NY 14853